systematic literature review vs meta analysis

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Systematic reviews vs meta-analysis: what’s the difference?

Posted on 24th July 2023 by Verónica Tanco Tellechea

You may hear the terms ‘systematic review’ and ‘meta-analysis being used interchangeably’. Although they are related, they are distinctly different. Learn more in this blog for beginners.

What is a systematic review?

According to Cochrane (1), a systematic review attempts to identify, appraise and synthesize all the empirical evidence to answer a specific research question. Thus, a systematic review is where you might find the most relevant, adequate, and current information regarding a specific topic. In the levels of evidence pyramid , systematic reviews are only surpassed by meta-analyses. 

To conduct a systematic review, you will need, among other things: 

• A specific research question, usually in the form of a PICO question.
• Pre-specified eligibility criteria, to decide which articles will be included or discarded from the review. 
• To follow a systematic method that will minimize bias.

You can find protocols that will guide you from both Cochrane and the Equator Network , among other places, and if you are a beginner to the topic then have a read of an overview about systematic reviews.

What is a meta-analysis?

A meta-analysis is a quantitative, epidemiological study design used to systematically assess the results of previous research (2) . Usually, they are based on randomized controlled trials, though not always. This means that a meta-analysis is a mathematical tool that allows researchers to mathematically combine outcomes from multiple studies.

When can a meta-analysis be implemented?

There is always the possibility of conducting a meta-analysis, yet, for it to throw the best possible results it should be performed when the studies included in the systematic review are of good quality, similar designs, and have similar outcome measures.

Why are meta-analyses important?

Outcomes from a meta-analysis may provide more precise information regarding the estimate of the effect of what is being studied because it merges outcomes from multiple studies. In a meta-analysis, data from various trials are combined and generate an average result (1), which is portrayed in a forest plot diagram. Moreover, meta-analysis also include a funnel plot diagram to visually detect publication bias.

Conclusions

A systematic review is an article that synthesizes available evidence on a certain topic utilizing a specific research question, pre-specified eligibility criteria for including articles, and a systematic method for its production. Whereas a meta-analysis is a quantitative, epidemiological study design used to assess the results of articles included in a systematic-review. 

Remember: All meta-analyses involve a systematic review, but not all systematic reviews involve a meta-analysis.

If you would like some further reading on this topic, we suggest the following:

The systematic review – a S4BE blog article

Meta-analysis: what, why, and how – a S4BE blog article

The difference between a systematic review and a meta-analysis – a blog article via Covidence

Systematic review vs meta-analysis: what’s the difference? A 5-minute video from Research Masterminds:

• About Cochrane reviews [Internet]. Cochranelibrary.com. [cited 2023 Apr 30]. Available from: https://www.cochranelibrary.com/about/about-cochrane-reviews
• Haidich AB. Meta-analysis in medical research. Hippokratia. 2010;14(Suppl 1):29–37.

Verónica Tanco Tellechea

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The difference between a systematic review and a meta-analysis

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Covidence explains the difference between systematic review & meta-analysis.

Systematic review and meta-analysis are two terms that you might see used interchangeably. Each term refers to research about research, but there are important differences!

A systematic review is a piece of work that asks a research question and then answers it by summarising the evidence that meets a set of pre-specified criteria. Some systematic reviews present their results using meta-analysis, a statistical method that combines the results of several trials to generate an average result. Meta-analysis adds value because it can produce a more precise estimate of the effect of a treatment than considering each study individually 🎯.

Let’s take a look at a few related questions that you might have about systematic reviews and meta-analysis.

🙋🏽‍♂️ What are the stages of a systematic review?

A systematic review starts with a research question and a protocol or research plan. A review team searches for studies to answer the question using a highly sensitive search strategy. The retrieved studies are then screened for eligibility using the inclusion and exclusion criteria (this is done by at least two people working independently). Next, the reviewers extract the relevant data and assess the quality of the included studies. Finally, the review team synthesises the extracted study data (perhaps using meta-analysis) and presents the results. The process is shown in figure 1.

Covidence helps researchers complete systematic review quickly and easily! It supports reviewers with study selection, data extraction and quality assessment. Data exported from Covidence can be saved in Excel for reliable transfer to your choice of data analysis software or, if you’re writing a Cochrane Review, to RevMan 5.

🙋🏻‍♀️ What does 'systematic' actually mean?

In this context, systematic means that the methods used to search for and analyse the data are

transparent, reproducible and defined before searching begins. This is what differentiates a systematic review from a descriptive review that might be based on, for example, a subset of the literature that the author is familiar with at the time of writing. Systematic reviews strive to be as thorough and rigorous as possible to minimise the bias that would result from cherry-picking studies in a non-systematic way. Systematic reviews sit at the top of the evidence hierarchy because it is widely agreed that studies with rigorous methods are those best able to minimise the risk of bias on the results of the study. This is what makes systematic reviews the most reliable form of evidence (see figure 2). 

🙋🏾‍♂️ Why don't all systematic reviews use meta-analysis?

Meta-analysis can improve the precision of an effect estimate. But it can also be misleading if it is performed with data that are not sufficiently similar, or with data whose methodological quality is poor (for example, because the study participants were not properly randomized). So it’s not always appropriate to use meta-analysis and many systematic reviews do not include them. Reviews that do not contain meta-analysis can still synthesise study data to produce something that has greater value than the sum of its parts.

🙋🏾‍♀️ What does meta-analysis do?

Meta-analysis produces a more precise estimate of treatment effect. There are several types of effect size and the most suitable type is chosen by the review team based on the type of outcomes and interventions under investigation. Typical effect sizes in systematic reviews are the odds ratio, the risk ratio, the weighted mean difference and the standardized mean difference. The results of a meta-analysis are displayed using a forest plot like the one in figure 3.

Some meta-analyses also include subgroup analysis or meta-regression. These techniques are used to explore a factor (for example, the age of the study participant) that might influence the relationship between the treatment and the intervention. Plans to analyse the data using these techniques should be described and justified before looking at the data, ideally at the research plan or protocol stage, to avoid introducing bias. Like meta-analysis, subgroup analysis and meta-regression are advisable only in certain circumstances.

Systematic reviewer pro-tip

  Think carefully before you plan subgroup analysis or meta-regression and always ask a methodologist for advice

🙋🏼‍♀️ What are the other ways to synthesise evidence?

Systematic reviews combine study data in a number of ways to reach an overall understanding of the evidence. Meta-analysis is a type of statistical synthesis. Narrative synthesis combines the findings of multiple studies using words. All systematic reviews, including those that use meta-analysis, are likely to contain an element of narrative synthesis by summarising in words the evidence included in the review. But narrative synthesis doesn’t just describe the included studies: it also seeks to explain the gathered evidence, for example by looking at similarities and differences between the study findings and by exploring possible reasons for those similarities and differences in a systematic way. Narrative synthesis should not be confused with narrative review, which is a term sometimes used for a non-systematic review of the literature (for example in a textbook chapter) where there is no systematic attempt to address issues of bias.

There are many types of systematic review . What they all have in common is the use of transparent and reproducible methods that are defined before the search begins. There is no ‘best’ way to synthesise systematic review evidence, and the most suitable approach will depend on factors such as the nature of the review question, the type of intervention and the outcomes of interest.

Covidence is a web-based tool that saves you time at the screening, selection, data extraction and quality assessment stages of your review. It provides easy collaboration across teams and a clear overview of task status, helping you to efficiently complete your review. Sign up for a free trial today! 😀

1 Effectiveness of psychosocial interventions for reducing parental substance misuse – McGovern, R – 2021 | Cochrane Library https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD012823.pub2/full .  Accessed 25 March 2021

Laura Mellor. Portsmouth, UK

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Systematic Reviews and Meta Analysis

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Systematic review Q & A

What is a systematic review.

A systematic review is guided filtering and synthesis of all available evidence addressing a specific, focused research question, generally about a specific intervention or exposure. The use of standardized, systematic methods and pre-selected eligibility criteria reduce the risk of bias in identifying, selecting and analyzing relevant studies. A well-designed systematic review includes clear objectives, pre-selected criteria for identifying eligible studies, an explicit methodology, a thorough and reproducible search of the literature, an assessment of the validity or risk of bias of each included study, and a systematic synthesis, analysis and presentation of the findings of the included studies. A systematic review may include a meta-analysis.

For details about carrying out systematic reviews, see the Guides and Standards section of this guide.

Is my research topic appropriate for systematic review methods?

A systematic review is best deployed to test a specific hypothesis about a healthcare or public health intervention or exposure. By focusing on a single intervention or a few specific interventions for a particular condition, the investigator can ensure a manageable results set. Moreover, examining a single or small set of related interventions, exposures, or outcomes, will simplify the assessment of studies and the synthesis of the findings.

Systematic reviews are poor tools for hypothesis generation: for instance, to determine what interventions have been used to increase the awareness and acceptability of a vaccine or to investigate the ways that predictive analytics have been used in health care management. In the first case, we don't know what interventions to search for and so have to screen all the articles about awareness and acceptability. In the second, there is no agreed on set of methods that make up predictive analytics, and health care management is far too broad. The search will necessarily be incomplete, vague and very large all at the same time. In most cases, reviews without clearly and exactly specified populations, interventions, exposures, and outcomes will produce results sets that quickly outstrip the resources of a small team and offer no consistent way to assess and synthesize findings from the studies that are identified.

If not a systematic review, then what?

You might consider performing a scoping review . This framework allows iterative searching over a reduced number of data sources and no requirement to assess individual studies for risk of bias. The framework includes built-in mechanisms to adjust the analysis as the work progresses and more is learned about the topic. A scoping review won't help you limit the number of records you'll need to screen (broad questions lead to large results sets) but may give you means of dealing with a large set of results.

This tool can help you decide what kind of review is right for your question.

Can my student complete a systematic review during her summer project?

Probably not. Systematic reviews are a lot of work. Including creating the protocol, building and running a quality search, collecting all the papers, evaluating the studies that meet the inclusion criteria and extracting and analyzing the summary data, a well done review can require dozens to hundreds of hours of work that can span several months. Moreover, a systematic review requires subject expertise, statistical support and a librarian to help design and run the search. Be aware that librarians sometimes have queues for their search time. It may take several weeks to complete and run a search. Moreover, all guidelines for carrying out systematic reviews recommend that at least two subject experts screen the studies identified in the search. The first round of screening can consume 1 hour per screener for every 100-200 records. A systematic review is a labor-intensive team effort.

How can I know if my topic has been been reviewed already?

Before starting out on a systematic review, check to see if someone has done it already. In PubMed you can use the systematic review subset to limit to a broad group of papers that is enriched for systematic reviews. You can invoke the subset by selecting if from the Article Types filters to the left of your PubMed results, or you can append AND systematic[sb] to your search. For example:

"neoadjuvant chemotherapy" AND systematic[sb]

The systematic review subset is very noisy, however. To quickly focus on systematic reviews (knowing that you may be missing some), simply search for the word systematic in the title:

"neoadjuvant chemotherapy" AND systematic[ti]

Any PRISMA-compliant systematic review will be captured by this method since including the words "systematic review" in the title is a requirement of the PRISMA checklist. Cochrane systematic reviews do not include 'systematic' in the title, however. It's worth checking the Cochrane Database of Systematic Reviews independently.

You can also search for protocols that will indicate that another group has set out on a similar project. Many investigators will register their protocols in PROSPERO , a registry of review protocols. Other published protocols as well as Cochrane Review protocols appear in the Cochrane Methodology Register, a part of the Cochrane Library .

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A systematic review collects and analyzes all evidence that answers a specific research question. In a systematic review, a question needs to be clearly defined and have inclusion and exclusion criteria. In general, specific and systematic methods selected are intended to minimize bias. This is followed by an extensive search of the literature and a critical analysis of the search results. The reason why a systematic review is conducted is to provide a current evidence-based answer to a specific question that in turn helps to inform decision making. Check out the Centers for Disease Control and Prevention and Cochrane Reviews links to learn more about Systematic Reviews.

A systematic review can be combined with a meta-analysis. A meta-analysis is the use of statistical methods to summarize the results of a systematic review. Not every systematic review contains a meta-analysis. A meta-analysis may not be appropriate if the designs of the studies are too different, if there are concerns about the quality of studies, if the outcomes measured are not sufficiently similar for the result across the studies to be meaningful.

Centers for Disease Control and Prevention. (n.d.).  Systematic Reviews . Retrieved from  https://www.cdc.gov/library/researchguides/sytemsaticreviews.html

Cochrane Library. (n.d.).  About Cochrane Reviews . Retrieved from  https://www.cochranelibrary.com/about/about-cochrane-reviews

Source: Kysh, Lynn (2013): Difference between a systematic review and a literature review. [figshare]. Available at:  https://figshare.com/articles/Difference_between_a_systematic_review_and_a_literature_review/766364

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Understanding the Differences Between a Systematic Review vs Meta Analysis

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The advent of evidence-based medicine has increased the demand for systematic methods to analyze and synthesize clinical evidence. When it comes to the search for the best available clinical evidence, randomized control trials, systematic reviews, and meta-analysis are considered the “gold standard” [1].

Since both systematic reviews and meta-analyses are secondary research approaches (research of research), sometimes the terms are used interchangeably, but there are vast differences between them.

A systematic review is a review that collects, critically appraises, and synthesizes all the available evidence to answer a specifically formulated research question.

A meta-analysis, on the other hand, is a statistical method that is used to pool results from various independent studies, to generate an overall estimate of the studied phenomenon.

Systematic reviews can sometimes use meta-analysis to synthesize their results, but they are two very distinct techniques. In this article, we will look at the definition of a systematic review , and understand how it is different from a meta-analysis.

What Is A Systematic Review?

In section 1.2.2 of the Cochrane Handbook, titled What is a systematic review?, the following definition can be found, “A systematic review attempts to collate all empirical evidence that fits the pre-specified eligibility criteria in order to answer a specific research question. It uses explicit, systematic methods that are selected with a view to minimizing bias, thus providing more reliable findings from which conclusions can be drawn and decisions made (Antman 1992, Oxman 1993). The key characteristics of a systematic review are: a clearly stated set of objectives with pre-defined eligibility criteria for the studies; an explicit, reproducible methodology; a systematic search that attempts to identify all the studies that would meet the eligibility criteria; an assessment of the validity of the findings of the included studies, for example through the assessment of the risk of bias; and a systematic presentation, and synthesis, of the characteristics and findings of the included studies”[2].

The evidence collected in a systematic review can be analyzed and synthesized, quantitatively, or qualitatively. The quantitative analysis of empirical evidence can use a meta-analysis as the statistical approach. To know more about how to write a systematic review , you can read our article; previously linked.

What Is Meta-Analysis?

Meta-analysis is a statistical method used to combine the results of individual studies. It uses a quantitative, formal, and epidemiological study design to systematically assess the results of previous studies to derive conclusions about a specific research parameter [3]. It is therefore an approach for systematically combining pertinent qualitative and quantitative study data from several included studies to establish a single conclusion that has significant statistical power.

Typically, the primary studies included in a meta-analysis are randomized controlled trials (RCTs). In a meta-analysis, the main objective is to provide more precise estimates of the effects of a treatment or of a risk factor for a disease, than any of the individual studies included in the pooled analysis. The data is also analyzed for heterogeneity (variation within outcomes), and generalizability (similarities between outcomes) within the individual studies, which facilitates more effective clinical decision making. Examining the heterogeneity of effect estimates within the primary studies is perhaps the most important task in a meta-analysis.

Meta-analyses of observational studies such as cohort studies are frequently performed, but no widely accepted guidance is available at the moment. While these meta-analyses are frequently published in literature, they are considered suboptimal to those involving RCTs.  The main reason is that the observational studies may entail an increased risk of biases and high levels of heterogeneity. Researchers who have to conduct meta-analyses on observational studies ought to carefully consider whether all included studies are able to answer the same clinical question.

Although meta-analysis is a subset of systematic reviews, a systematic review may or may not include a meta-analysis. An advantage of meta-analysis is that it has the ability to be completely objective in evaluating the research parameter. However, not all research areas have enough evidence to allow a meta-analysis. The inclusion of meta-analysis in a systematic review depends on the research question, the intervention to be studied, and the desired outcomes.

• Sur RL, Dahm P. History of evidence-based medicine. Indian journal of urology: IJU: journal of the Urological Society of India. 2011;27(4):487–9.
• Clarke M, Chalmers I. Discussion sections in reports of controlled trials published in general medical journals: islands in search of continents? Jama. 1998;280(3):280–2.
• Haidich AB. Meta-analysis in medical research. Hippokratia. 2010;14(Suppl 1):29-37.

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Reproduced from Grant, M. J. and Booth, A. (2009), A typology of reviews: an analysis of 14 review types and associated methodologies. Health Information & Libraries Journal, 26: 91–108. doi:10.1111/j.1471-1842.2009.00848.x

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Literature Review, Systematic Review and Meta-analysis

Literature reviews can be a good way to narrow down theoretical interests; refine a research question; understand contemporary debates; and orientate a particular research project. It is very common for PhD theses to contain some element of reviewing the literature around a particular topic. It’s typical to have an entire chapter devoted to reporting the result of this task, identifying gaps in the literature and framing the collection of additional data.

Systematic review is a type of literature review that uses systematic methods to collect secondary data, critically appraise research studies, and synthesise findings. Systematic reviews are designed to provide a comprehensive, exhaustive summary of current theories and/or evidence and published research (Siddaway, Wood & Hedges, 2019) and may be qualitative or qualitative. Relevant studies and literature are identified through a research question, summarised and synthesized into a discrete set of findings or a description of the state-of-the-art. This might result in a ‘literature review’ chapter in a doctoral thesis, but can also be the basis of an entire research project.

Meta-analysis is a specialised type of systematic review which is quantitative and rigorous, often comparing data and results across multiple similar studies. This is a common approach in medical research where several papers might report the results of trials of a particular treatment, for instance. The meta-analysis then statistical techniques to synthesize these into one summary. This can have a high statistical power but care must be taken not to introduce bias in the selection and filtering of evidence.

Whichever type of review is employed, the process is similarly linear. The first step is to frame a question which can guide the review. This is used to identify relevant literature, often through searching subject-specific scientific databases. From these results the most relevant will be identified. Filtering is important here as there will be time constraints that prevent the researcher considering every possible piece of evidence or theoretical viewpoint. Once a concrete evidence base has been identified, the researcher extracts relevant data before reporting the synthesized results in an extended piece of writing.

Literature Review: GO-GN Insights

Sarah Lambert used a systematic review of literature with both qualitative and quantitative phases to investigate the question “How can open education programs be reconceptualised as acts of social justice to improve the access, participation and success of those who are traditionally excluded from higher education knowledge and skills?”

“My PhD research used systematic review, qualitative synthesis, case study and discourse analysis techniques, each was underpinned and made coherent by a consistent critical inquiry methodology and an overarching research question. “Systematic reviews are becoming increasingly popular as a way to collect evidence of what works across multiple contexts and can be said to address some of the weaknesses of case study designs which provide detail about a particular context – but which is often not replicable in other socio-cultural contexts (such as other countries or states.) Publication of systematic reviews that are done according to well defined methods are quite likely to be published in high-ranking journals – my PhD supervisors were keen on this from the outset and I was encouraged along this path. “Previously I had explored social realist authors and a social realist approach to systematic reviews (Pawson on realist reviews) but they did not sufficiently embrace social relations, issues of power, inclusion/exclusion. My supervisors had pushed me to explain what kind of realist review I intended to undertake, and I found out there was a branch of critical realism which was briefly of interest. By getting deeply into theory and trying out ways of combining theory I also feel that I have developed a deeper understanding of conceptual working and the different ways theories can be used at all stagesof research and even how to come up with novel conceptual frameworks.”

Useful references for Systematic Review & Meta-Analysis: Finfgeld-Connett (2014); Lambert (2020); Siddaway, Wood & Hedges (2019)

Research Methods Handbook Copyright © 2020 by Rob Farrow; Francisco Iniesto; Martin Weller; and Rebecca Pitt is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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Systematic Literature Review or Literature Review?

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Table of Contents

As a researcher, you may be required to conduct a literature review. But what kind of review do you need to complete? Is it a systematic literature review or a standard literature review? In this article, we’ll outline the purpose of a systematic literature review, the difference between literature review and systematic review, and other important aspects of systematic literature reviews.

What is a Systematic Literature Review?

The purpose of systematic literature reviews is simple. Essentially, it is to provide a high-level of a particular research question. This question, in and of itself, is highly focused to match the review of the literature related to the topic at hand. For example, a focused question related to medical or clinical outcomes.

The components of a systematic literature review are quite different from the standard literature review research theses that most of us are used to (more on this below). And because of the specificity of the research question, typically a systematic literature review involves more than one primary author. There’s more work related to a systematic literature review, so it makes sense to divide the work among two or three (or even more) researchers.

Your systematic literature review will follow very clear and defined protocols that are decided on prior to any review. This involves extensive planning, and a deliberately designed search strategy that is in tune with the specific research question. Every aspect of a systematic literature review, including the research protocols, which databases are used, and dates of each search, must be transparent so that other researchers can be assured that the systematic literature review is comprehensive and focused.

Most systematic literature reviews originated in the world of medicine science. Now, they also include any evidence-based research questions. In addition to the focus and transparency of these types of reviews, additional aspects of a quality systematic literature review includes:

• Clear and concise review and summary
• Comprehensive coverage of the topic
• Accessibility and equality of the research reviewed

Systematic Review vs Literature Review

The difference between literature review and systematic review comes back to the initial research question. Whereas the systematic review is very specific and focused, the standard literature review is much more general. The components of a literature review, for example, are similar to any other research paper. That is, it includes an introduction, description of the methods used, a discussion and conclusion, as well as a reference list or bibliography.

A systematic review, however, includes entirely different components that reflect the specificity of its research question, and the requirement for transparency and inclusion. For instance, the systematic review will include:

• Eligibility criteria for included research
• A description of the systematic research search strategy
• An assessment of the validity of reviewed research
• Interpretations of the results of research included in the review

As you can see, contrary to the general overview or summary of a topic, the systematic literature review includes much more detail and work to compile than a standard literature review. Indeed, it can take years to conduct and write a systematic literature review. But the information that practitioners and other researchers can glean from a systematic literature review is, by its very nature, exceptionally valuable.

This is not to diminish the value of the standard literature review. The importance of literature reviews in research writing is discussed in this article . It’s just that the two types of research reviews answer different questions, and, therefore, have different purposes and roles in the world of research and evidence-based writing.

Systematic Literature Review vs Meta Analysis

It would be understandable to think that a systematic literature review is similar to a meta analysis. But, whereas a systematic review can include several research studies to answer a specific question, typically a meta analysis includes a comparison of different studies to suss out any inconsistencies or discrepancies. For more about this topic, check out Systematic Review VS Meta-Analysis article.

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Meta-analysis vs Systematic review: Differences, Similarities, and 9 Simple Steps to Write

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Meta-analysis and systematic review are two types of research methods commonly used in scientific literature to summarize and synthesize existing evidence on a particular topic. Both methods aim to provide a comprehensive and objective summary of the available evidence, but they differ in their approach and the type of data they analyze. In this blog post, we will explore meta-analysis vs systematic review, with thier differences, similarities, advantages, limitations, how to write, and how to decide which method to use in your research.

Table of Contents

What is a Meta-Analysis?

A meta-analysis is a statistical method used to combine the results of multiple studies on a particular topic. It involves a systematic review of the literature, similar to a systematic review, but also includes a quantitative analysis of the results. Meta-analyses use statistical techniques to pool the results of individual studies, calculate summary effect sizes, and assess the overall strength of the evidence.

Meta-analysis can be conducted using different statistical methods, depending on the type of data and the research question. The most common methods include fixed-effects models and random-effects models. Fixed-effects models assume that all studies are estimating the same effect size, while random-effects models account for variability in the effect size across studies.

Advantages of Meta-Analysis:

• Provides a quantitative summary of the available evidence
• Increases statistical power by combining multiple studies
• Can identify small but significant effects that may not be detectable in individual studies
• Can assess the consistency of the results across studies
• Can explore sources of heterogeneity and perform subgroup analyses

Limitations of Meta-Analysis:

• Requires a sufficient number of studies with similar designs and outcomes
• May be limited by the quality of the included studies
• May be influenced by publication bias and selective reporting of outcomes
• Can be complex to interpret, particularly if the studies are heterogeneous

How to Write Meta-Analysis?

Writing a meta-analysis can be a complex and time-consuming process, but it is an important way to synthesize and analyze the results of multiple studies on a particular topic. Here are the steps to follow when writing a meta-analysis:

• Define the research question: Start by defining the research question and the inclusion and exclusion criteria for the studies to be included in the meta-analysis. This will help guide your search and ensure that you are including relevant studies.
• Conduct a comprehensive search: Conduct a comprehensive search of multiple databases, including PubMed , Embase , and the Cochrane Library  using a combination of keywords and MeSH terms related to your research question. It is important to include both published and unpublished studies to minimize publication bias.
• Screen the articles: After conducting the search, screen the articles for eligibility based on the inclusion and exclusion criteria. Start by screening the titles and abstracts, and then move on to the full-text articles. Keep track of the reasons for exclusion.
• Extract the data: Once you have identified the studies to be included in the meta-analysis, extract the data from each study, including study design, population characteristics, interventions, outcomes, and results. This data should be recorded in a standardized data extraction form to ensure consistency and accuracy.
• Assess the quality of the studies: Assess the quality of the studies using a standardized tool, such as the Cochrane Risk of Bias Tool, to evaluate the risk of bias and the overall quality of the evidence.
• Conduct statistical analysis: Conduct statistical analysis on the data extracted from the included studies, using appropriate methods such as fixed-effect or random-effects models to calculate summary effect sizes.
• Evaluate heterogeneity: Evaluate heterogeneity among the included studies using appropriate methods, such as the I2 statistic, to determine the degree of variation in effect sizes across studies.
• Conduct sensitivity analysis: Conduct sensitivity analysis to explore the robustness of the results to different assumptions or methods used in the analysis.
• Interpret the results: Interpret the results of the meta-analysis, taking into account the quality of the evidence, the degree of heterogeneity, and any limitations or gaps in the literature.
• Write the manuscript: Write the manuscript for the meta-analysis, following the guidelines for meta-analyses set by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The manuscript should include an introduction, methods, results, discussion, and conclusions.
• Peer review and publication: Submit the manuscript for peer review and make revisions as necessary. Once the manuscript has been accepted for publication, make sure to follow the guidelines for reporting meta-analyses in the journal.

Writing a meta-analysis can be a complex and time-consuming process, but it is an important way to synthesize and analyze the results of multiple studies on a particular topic. By following these steps, you can ensure that your meta-analysis is comprehensive, accurate, and informative.

To learn in detail about manuscript writing, read our blog on “How to write a manuscript for a Journal in 10 simple steps”

What is a Systematic Review?

A systematic review is a rigorous and systematic approach to reviewing the existing literature on a particular topic. It involves a comprehensive search of multiple databases to identify all relevant studies that meet predefined inclusion and exclusion criteria. The review process is guided by a protocol that outlines the research question, search strategy, inclusion and exclusion criteria, data extraction methods, and quality assessment criteria.

Systematic review provides a summary of the available evidence on a particular topic, but they do not combine the results of individual studies quantitatively. Instead, they provide a narrative synthesis of the findings, including a description of the study designs, population characteristics, interventions, and outcomes. Systematic review also assess the quality of the included studies, the risk of bias, and the strength of the evidence.

Advantages of Systematic Review:

• Comprehensive and rigorous approach to reviewing the evidence
• Minimizes bias and ensures the reproducibility of the results
• Provides a qualitative summary of the available evidence
• Can identify gaps in the literature and highlight areas for future research
• Systematic reviews provide a clear and transparent methodology
• Saves time and resources

Limitations of Systematic Review:

• Can be time-consuming and resource-intensive
• May be limited by the availability and quality of the existing literature
• May be limited by the heterogeneity of the included studies, making it difficult to draw definitive conclusions

How to Write Systematic Review?

Writing a systematic review can be a time-consuming and complex process, but it is an important way to summarize and synthesize existing evidence on a particular topic. Here are the steps to follow when writing a systematic review:

• Define the research question: Start by defining the research question and the inclusion and exclusion criteria for the studies to be included in the review. This will help guide your search and ensure that you are including relevant studies.
• Conduct a comprehensive search: Conduct a comprehensive search of multiple databases, including PubMed , Embase , and the Cochrane Library , using a combination of keywords and MeSH terms related to your research question. It is important to include both published and unpublished studies to minimize publication bias.
• Extract the data: Once you have identified the studies to be included in the review, extract the data from each study, including study design, population characteristics, interventions, outcomes, and results. This data should be recorded in a standardized data extraction form to ensure consistency and accuracy.
• Synthesize the findings: Synthesize the findings from the included studies by organizing the data according to the research question and using a narrative synthesis to describe the overall findings. This should include a description of the study designs, population characteristics, interventions, outcomes, and results.
• Draw conclusions: Draw conclusions based on the findings of the systematic review, taking into account the quality of the evidence, the consistency of the findings, and any limitations or gaps in the literature.
• Write the manuscript: Write the manuscript for the systematic review, following the guidelines for systematic reviews set by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The manuscript should include an introduction, methods, results, discussion, and conclusions.
• Peer review and publication: Submit the manuscript for peer review and make revisions as necessary. Once the manuscript has been accepted for publication, make sure to follow the guidelines for reporting systematic reviews in the journal.

Writing a systematic review can be a complex and time-consuming process, but it is an important way to summarize and synthesize existing evidence on a particular topic. By following these steps, you can ensure that your systematic review is comprehensive, accurate, and informative.

Meta-analysis vs systematic review

Key differences.

Meta-analysis and systematic reviews are two types of research synthesis that are commonly used in evidence-based practice. While they are similar in many ways, there are also key differences between them. Here are the main differences between meta-analysis and systematic review:

• Purpose: The purpose of a systematic review is to synthesize and summarize the available evidence on a particular research question or topic. A meta-analysis, on the other hand, goes a step further and uses statistical methods to combine the results of multiple studies into a single quantitative estimate of the effect size.
• Study selection: Both meta-analyses and systematic reviews involve a comprehensive search of the literature, but the criteria for selecting studies may differ. Systematic reviews may include all types of studies, including qualitative and observational studies, whereas meta-analyses typically focus on randomized controlled trials (RCTs) or other quantitative studies.
• Data extraction: In a systematic review, data are typically extracted from each included study in a qualitative manner, meaning that the results are described and summarized but not statistically combined. In a meta-analysis, on the other hand, data are extracted in a quantitative manner, with effect sizes and standard errors or confidence intervals calculated for each study.
• Statistical analysis: Systematic reviews do not typically involve statistical analysis beyond basic descriptive statistics, whereas meta-analyses use statistical methods to pool the results of the included studies and calculate summary effect sizes.
• Heterogeneity assessment: Both systematic reviews and meta-analyses may assess heterogeneity (i.e., variation in effect sizes across studies), but the methods used may differ. In a systematic review, heterogeneity may be assessed qualitatively through a narrative synthesis of the results. In a meta-analysis, statistical methods such as the I2 statistic may be used to quantify the degree of heterogeneity.
• Interpretation of results: The results of a systematic review are typically presented in a narrative format, whereas the results of a meta-analysis are presented both in narrative form and in quantitative terms (e.g., effect sizes and confidence intervals). The interpretation of the results may also differ, with systematic reviews focusing on the overall body of evidence and meta-analyses providing a more precise estimate of the effect size.

In summary, meta-analysis and systematic review are both important tools for synthesizing and summarizing the available evidence on a particular research question or topic. While they share many similarities, they also differ in their purpose, study selection criteria, data extraction and analysis methods, heterogeneity assessment, and interpretation of results. Understanding these differences is essential for selecting the appropriate research synthesis method for a given research question or topic.

Key Similarities

Meta-analysis and systematic review share some similarities in terms of their purpose and the process involved. Here are some key similarities between the two:

• Both are methods of evidence synthesis: Meta-analysis and systematic review are both methods used to systematically review, evaluate, and synthesize the available evidence on a specific research question.
• Both require a comprehensive literature search: Both methods require a comprehensive search of multiple databases to identify all relevant studies that address the research question.
• Both require a rigorous screening and selection process: Both methods require a rigorous screening and selection process to identify studies that meet specific inclusion criteria and exclude those that do not.
• Both require quality assessment of included studies: Both methods require the quality assessment of included studies to ensure that the studies are of high quality and meet specific methodological criteria.
• Both aim to provide an unbiased summary of the available evidence: Both methods aim to provide an unbiased summary of the available evidence on a specific research question, using a transparent and replicable methodology.
• Both aim to inform decision-making: Both methods aim to inform decision-making in research, policy, and practice by providing a comprehensive and rigorous summary of the available evidence.

In summary, meta-analysis and systematic review share many similarities in their purpose and process. Both methods aim to provide an evidence-based summary of the available evidence on a specific research question, using a comprehensive, transparent, and replicable methodology.

How to Decide Which Method to Use?

Deciding whether to conduct a systematic review or a meta-analysis (or both) depends on the research question and the available evidence. Here are some factors to consider when making this decision:

• Research question: The type of research question being asked is an important factor in deciding which method to use. If the research question is focused on summarizing the available evidence on a particular topic or intervention, a systematic review may be more appropriate. If the research question is focused on estimating the size of an effect or the strength of an association, a meta-analysis may be more appropriate.
• Availability of data: Meta-analyses require quantitative data from the included studies, typically in the form of effect sizes and standard errors or confidence intervals. If the available data are not quantitative, a meta-analysis may not be feasible. In this case, a systematic review that includes a narrative synthesis of the available evidence may be more appropriate.
• Homogeneity of studies: Meta-analyses assume that the included studies are homogeneous, meaning that they are similar enough in terms of the population, intervention, and outcomes to be combined statistically. If there is substantial heterogeneity between the included studies, a meta-analysis may not be appropriate. In this case, a systematic review that includes a narrative synthesis of the available evidence may be more appropriate.
• Quality of studies: The quality of the included studies is an important consideration in both systematic reviews and meta-analyses. If the quality of the included studies is low or there is a high risk of bias, the results of both types of reviews may be compromised. However, a systematic review may still be informative in this case, as it can provide a comprehensive summary of the available evidence, even if the quality is low.
• Time and resources: Conducting a meta-analysis is typically more time-consuming and resource-intensive than conducting a systematic review, as it requires more advanced statistical methods. If time and resources are limited, a systematic review may be more feasible.
• Audience: The intended audience for the review is another important factor to consider. If the audience is primarily clinicians or policy makers who need a broad overview of the available evidence, a systematic review may be more appropriate. If the audience is primarily researchers who need a more precise estimate of the effect size, a meta-analysis may be more appropriate.

In summary, deciding which method to use depends on a range of factors, including the research question, availability and homogeneity of data, quality of studies, time and resources, and intended audience. Careful consideration of these factors can help researchers choose the most appropriate method for their specific question and available evidence.

Meta-analysis and systematic review are two valuable methods for summarizing and synthesizing existing evidence on a particular topic. While both methods aim to provide an objective and comprehensive summary of the available evidence, they differ in their approach and the type of data they analyze. Meta-analysis provides a quantitative summary of the effect size and the overall strength of the evidence while systematic review provides a qualitative summary of the available evidence. By understanding the differences between these methods, researchers can choose the most appropriate method for their research question and contribute to the advancement of evidence-based medicine.

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Systematic Reviews and Meta-Analysis: A Guide for Beginners

Affiliation.

• 1 Department of Pediatrics, Advanced Pediatrics Centre, PGIMER, Chandigarh. Correspondence to: Prof Joseph L Mathew, Department of Pediatrics, Advanced Pediatrics Centre, PGIMER Chandigarh. [email protected].
• PMID: 34183469
• PMCID: PMC9065227
• DOI: 10.1007/s13312-022-2500-y

Systematic reviews involve the application of scientific methods to reduce bias in review of literature. The key components of a systematic review are a well-defined research question, comprehensive literature search to identify all studies that potentially address the question, systematic assembly of the studies that answer the question, critical appraisal of the methodological quality of the included studies, data extraction and analysis (with and without statistics), and considerations towards applicability of the evidence generated in a systematic review. These key features can be remembered as six 'A'; Ask, Access, Assimilate, Appraise, Analyze and Apply. Meta-analysis is a statistical tool that provides pooled estimates of effect from the data extracted from individual studies in the systematic review. The graphical output of meta-analysis is a forest plot which provides information on individual studies and the pooled effect. Systematic reviews of literature can be undertaken for all types of questions, and all types of study designs. This article highlights the key features of systematic reviews, and is designed to help readers understand and interpret them. It can also help to serve as a beginner's guide for both users and producers of systematic reviews and to appreciate some of the methodological issues.

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• Introduction
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Medium term indicates 1 year or less. Results are reported using inverse-variance weighted random-effects methods. MD indicates mean difference; RCT, randomized clinical trial. Size of diamond markers indicates weight.

Results are reported using inverse-variance weighted random-effects methods. RCT indicates randomized clinical trial; RR, risk raio. Size of diamond markers indicates weight.

Data are expressed as medium-term (≤1 year) Disabilities of the Arm, Shoulder and Hand questionnaire (DASH) score (operative vs nonoperative groups) according to mean age of the study population in a meta-analysis of distal radius fractures. Circles represent the different studies, with circle size corresponding to the study weight. The black line represents the null value. MD indicates mean difference.

eTable 1. Search Syntax Performed Last on June 15, 2019

eTable 2. Quality Assessment According to the MINORS Criteria in a Meta-analysis of Distal Radius Fractures

eTable 3. Treatment Characteristics of Included Studies in a Meta-analysis of Distal Radius Fractures

eTable 4. Quality Assessment of Included Studies in a Meta-analysis of Distal Radius Fractures

eTable 5. Functional Outcome Measures of Included Studies in a Meta-analysis of Distal Radius Fractures

eTable 6. Clinical Outcome Measures of Included Studies in a Meta-analysis of Distal Radius Fractures

eTable 7. Clinical Outcome Measures of Included Studies in a Meta-analysis of Distal Radius Fractures

eTable 8. Radiologic Outcome Measures of Included Studies in a Meta-analysis of Distal Radius Fractures

eFigure 1. PRISMA Flow Diagram Representing the Search and Selection of Studies Comparing Operative vs Nonoperative Treatment of Distal Radius Fractures

eFigure 2. Funnel Plot of Medium-Term (≤1 y) DASH Score in a Meta-analysis of Distal Radius Fractures

eFigure 3. Funnel Plot of Complication Rate in a Meta-analysis of Distal Radius Fractures

eFigure 4. Forest Plot of Long-Term (>1 y) DASH Score in a Meta-analysis of Distal Radius Fractures

eFigure 5. Forest Plot of Medium-Term (≤1 y) PRWE Score in a Meta-analysis of Distal Radius Fractures

eFigure 6. Forest Plot of Long-Term (>1 y) PRWE Score in a Meta-analysis of Distal Radius Fractures

eFigure 7. Forest Plot of Medium-Term (≤1 y) VAS Score in a Meta-analysis of Distal Radius Fractures

eFigure 8. Forest Plot of Long-Term (>1 y) VAS Score in a Meta-analysis of Distal Radius Fractures

eFigure 9. Forest Plot of Grip Strength in Kilograms in a Meta-analysis of Distal Radius Fractures

eFigure 10. Forest Plot of Grip Strength as Percentage of Unaffected Side in a Meta-analysis of Distal Radius Fractures

eFigure 11. Forest Plot of Range of Wrist Extension in Degrees in a Meta-analysis of Distal Radius Fractures

eFigure 12. Forest Plot of Range of Wrist Flexion in Degrees in a Meta-analysis of Distal Radius Fractures

eFigure 13. Forest Plot of Range of Wrist Pronation in Degrees in a Meta-analysis of Distal Radius Fractures

eFigure 14. Forest Plot of Range of Wrist Supination in Degrees in a Meta-analysis of Distal Radius Fractures

eFigure 15. Forest Plot of Radial Deviation in Degrees in a Meta-analysis of Distal Radius Fractures

eFigure 16. Forest Plot of Ulnar Deviation in Degrees in a Meta-analysis of Distal Radius Fractures

eFigure 17. Forest Plot of Volar Tilt in Degrees in a Meta-analysis of Distal Radius Fractures

eFigure 18. Forest Plot of Radial Inclination in Degrees in a Meta-analysis of Distal Radius Fractures

eFigure 19. Forest Plot of Radial Height in Millimeters in a Meta-analysis of Distal Radius Fractures

eFigure 20. Forest Plot Of Articular Step-off in Millimeters in a Meta-analysis of Distal Radius Fractures

eFigure 21. Forest Plot of Ulnar Variance in Millimeters in a Meta-analysis of Distal Radius Fractures

eFigure 22. Forest Plot of Medium-Term (≤1 y) DASH Score for Studies That Only Included Patients With Age >60 Years and Other Studies That Included Patients With Age ≥18 Years in a Meta-analysis of Distal Radius Fractures

eFigure 23. Forest Plot of Complication Rate for Studies That Only Included Patients With Age >60 Years and Other Studies That Included Patients With Age ≥18 Years in a Meta-analysis of Distal Radius Fractures

eFigure 24. Forest Plot of Medium-Term (≤1 y) DASH Score in High-Quality Studies in a Meta-analysis of Distal Radius Fractures

eFigure 25. Forest Plot of Complication Rate in High-Quality Studies in a Meta-analysis of Distal Radius Fractures

eFigure 26. Forest Plot of Medium-Term (≤1 y) DASH Score in Studies With a Study Period After 2008 in a Meta-analysis of Distal Radius Fractures

eFigure 27. Forest Plot of Complication Rate in Studies With a Study Period After 2008 in a Meta-analysis of Distal Radius Fractures

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Ochen Y , Peek J , van der Velde D, et al. Operative vs Nonoperative Treatment of Distal Radius Fractures in Adults : A Systematic Review and Meta-analysis . JAMA Netw Open. 2020;3(4):e203497. doi:10.1001/jamanetworkopen.2020.3497

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Operative vs Nonoperative Treatment of Distal Radius Fractures in Adults : A Systematic Review and Meta-analysis

• 1 Department of Orthopedic Surgery, Harvard Medical School Orthopedic Trauma Initiative, Massachusetts General Hospital, Boston
• 2 Department of Surgery, University Medical Center Utrecht, Utrecht, the Netherlands
• 3 Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
• 4 Department of Surgery, St Antonius Hospital, Nieuwegein, the Netherlands
• 5 Department of Surgery, Luzerner Kantonsspital, Luzern, Switzerland
• 6 Department of Surgery, Diakonessenhuis Utrecht, Utrecht, the Netherlands

Question   What outcomes are associated with operative vs nonoperative treatment of distal radius fractures in adults?

Findings   This meta-analysis of 2254 unique participants in 23 unique studies showed that operative treatment of distal radius fractures improved the medium-term Disabilities of the Arm, Shoulder and Hand questionnaire score and grip strength compared with nonoperative treatment in adults, with no difference in overall complication rate.

Meaning   These findings suggest that operative treatment might be preferred for distal radius fractures.

Importance   No consensus has been reached to date regarding the optimal treatment for distal radius fractures. The international rate of operative treatment has been increasing, despite higher costs and limited functional outcome evidence to support this shift.

Objectives   To compare functional, clinical, and radiologic outcomes after operative vs nonoperative treatment of distal radius fractures in adults.

Data Sources   The PubMed/MEDLINE, Embase, CENTRAL (Cochrane Central Register of Controlled Trials), and CINAHL (Cumulative Index to Nursing and Allied Health Literature) databases were searched from inception to June 15, 2019, for studies comparing operative vs nonoperative treatment of distal radius fractures.

Study Selection   Randomized clinical trials (RCTs) and observational studies reporting on the following: acute distal radius fracture with operative treatment (internal or external fixation) vs nonoperative treatment (cast immobilization, splinting, or bracing); patients 18 years or older; and functional outcome. Studies in a language other than English or reporting treatment for refracture were excluded.

Data Extraction and Synthesis   Data extraction was performed independently by 2 reviewers. Effect estimates were pooled using random-effects models and presented as risk ratios (RRs) or mean differences (MDs) with 95% CIs. Data were analyzed in September 2019.

Main Outcomes and Measures   The primary outcome measures included medium-term functional outcome measured with the Disabilities of the Arm, Shoulder and Hand questionnaire (DASH) and the overall complication rate after operative and nonoperative treatment.

Results   A total of 23 unique studies were included, consisting of 8 RCTs and 15 observational studies, that described 2254 unique patients. Among the studies that presented sex data, 1769 patients were women [80.6%]. Overall weighted mean age was 67 [range, 22-90] years). The RCTs included 656 patients (29.1%); observational studies, 1598 patients (70.9%). The overall pooled effect estimates the showed a significant improvement in medium-term (≤1 year) DASH score after operative treatment compared with nonoperative treatment (MD, −5.22 [95% CI, −8.87 to −1.57]; P  = .005; I 2  = 84%). No difference in complication rate was observed (RR, 1.03 [95% CI, 0.69-1.55]; P  = .87; I 2  = 62%). A significant improvement in grip strength was noted after operative treatment, measured in kilograms (MD, 2.73 [95% CI, 0.15-5.32]; P  = .04; I 2  = 79%) and as a percentage of the unaffected side (MD, 8.21 [95% CI, 2.26-14.15]; P  = .007; I 2  = 76%). No improvement in medium-term DASH score was found in the subgroup of studies that only included patients 60 years or older (MD, −0.98 [95% CI, −3.52 to 1.57]; P  = .45; I 2  = 34%]), compared with a larger improvement in medium-term DASH score after operative treatment in the other studies that included patients 18 years or older (MD, −7.50 [95% CI, −12.40 to −2.60]; P  = .003; I 2  = 77%); the difference between these subgroups was statically significant (test for subgroup differences, P  = .02).

Conclusions and Relevance   This meta-analysis suggests that operative treatment of distal radius fractures improves the medium-term DASH score and grip strength compared with nonoperative treatment in adults, with no difference in overall complication rate. The findings suggest that operative treatment might be more effective and have a greater effect on the health and well-being of younger, nonelderly patients.

The fracture of the distal radius is the most common injury in adults, accounting for approximately 17.5% of fractures. 1 Distal radius fractures have a bimodal age distribution in the population, with a peak incidence seen in patients younger than 18 years and a second peak in patients 50 years or older. Recent studies indicate the worldwide incidence of distal radius fractures is increasing each year owing to the overall potential to live longer with comorbidities such as osteoporosis. 2 Although the elderly population is at greatest risk, distal radius fractures still have a significant effect on the health and well-being of nonelderly adults. Reports have shown a significant increase of distal radius fractures in patients aged 17 to 64 years. 2

The management of distal radius fractures consists of operative or nonoperative treatment. However, no consensus has been reached regarding the optimal treatment method. Several meta-analyses have been published on the comparison between operative and nonoperative treatment. 3 - 5 Recent meta-analyses have focused specifically on patient populations 60 years or older. 4 , 5 These meta-analyses found no difference in functional outcome between operative and nonoperative treatment in elderly patients. However, the international rate of operative treatment of distal radius fractures has been increasing, despite higher cost and limited functional outcome evidence to support this shift. 6

At present, no meta-analysis, to our knowledge, has evaluated functional outcome in patients younger than 60 years by including all patients 18 years or older. Moreover, the high incidence of distal radius fractures and the inconsistencies in treatment practices indicate further investigation is warranted to understand current treatment methods and outcomes. 7

Randomized clinical trials (RCTs) and observational studies are both increasingly used in orthopedic trauma meta-analyses for the evaluation of treatment effects. 8 - 12 Growing evidence shows that meta-analyses of RCTs and observational studies can be of value compared with meta-analyses of RCTs alone. Provided that observational studies are of high quality, the addition of observational studies in meta-analyses increases sample size and might provide a better insight into small treatment effects and infrequent outcome measures. Furthermore, observational studies might provide insight into treatment effects in a more heterogeneous patient population compared with the usually highly selected patient populations in RCTs. 13 - 18 The addition of observational studies in this meta-analysis could increase sample size and heterogeneity in patient characteristics, which could lead to the evaluation of different age groups, compared with the previous highly selected meta-analyses focusing on the elderly.

The primary aim of this systematic review and meta-analysis was to compare functional, clinical, and radiologic outcomes after operative vs nonoperative treatment of distal radius fractures in adults. As a secondary aim, we sought to compare outcomes in studies that only included patients 60 years or older and other studies that included patients 18 years or older. Finally, we compared effect estimates from RCTs and observational studies.

This systematic review and meta-analysis was performed and reported according to the Meta-analysis of Observational Studies in Epidemiology ( MOOSE ) and the Preferred Reporting Items for Systematic Reviews and Meta-analyses ( PRISMA ) reporting guidelines. 19 - 21 This review of the literature did not require approval from the independent ethics committee or institutional review board of the participating institutions.

The PubMed/MEDLINE, Embase, CENTRAL (Cochrane Central Register of Controlled Trials), and CINAHL (Cumulative Index to Nursing and Allied Health Literature) databases were searched from inception to June 15, 2019, for studies comparing operative vs nonoperative treatment of distal radius fractures by 2 reviewers (Y.O. and J.P.). The search syntax is provided in eTable 1 in the Supplement . Duplicate articles were removed, and 2 reviewers (Y.O. and J.P.) independently performed title and abstract screening for eligibility of identified studies. All published comparative studies, including RCTs and observational studies, reporting on the comparison of operative vs nonoperative treatment of distal radius fractures were eligible for inclusion.

After title and abstract screening, full-text articles were reviewed independently by the same 2 reviewers (Y.O. and J.P.). Inclusion criteria consisted of (1) acute distal radius fracture, (2) operative treatment (internal or external fixation) vs nonoperative treatment (cast immobilization, splinting, or bracing), (3) patients 18 years or older, and (4) reporting of functional outcome. Exclusion criteria consisted of (1) treatment for refracture, (2) language other than English, (3) no availability of full text, and (4) letters, meeting proceedings, and case reports. Disagreements on eligibility of full-text articles were resolved by consensus or by discussion with a third reviewer (M.H.). References of included studies were screened, and backward citation tracking was performed using Web of Science to identify articles not found in the original literature search.

Data extraction was performed independently by 2 reviewers (Y.O. and J.P.) with the use of a predefined data extraction form. The following characteristics were extracted from the included studies: first author, year of publication, study design, country in which the study was performed, study period, number of included patients, follow-up period, included age groups, AO fracture classification, operative method, and nonoperative method. Studies reporting on patient cohorts described in previously published articles were excluded or merged.

The methodological quality of included studies was independently assessed by 2 reviewers (Y.O. and J.P.) using the Methodological Index for Non-randomized Studies (MINORS). 22 The MINORS is a validated instrument for the assessment of methodological quality and clear reporting of nonrandomized surgical studies, resulting in a score ranging from 0 to 24 (higher scores indicate better quality) for comparative studies. 22 Details on the methodological quality assessment are provided in eTable 2 in the Supplement . Disagreements were resolved by consensus.

The primary outcome measures included medium-term functional outcome measured with the Disabilities of the Arm, Shoulder and Hand questionnaire (DASH) and the overall complication rate after operative and nonoperative treatment. The DASH is a patient-reported outcome instrument developed to measure upper extremity disability and symptoms, resulting in a score ranging from no disability (0) to most severe disability (100). 23 Functional outcome scores were subdivided according to follow-up as medium term (≤1 year) and long term (>1 year). Complication rate was defined as the overall rate of complications and included reports of infection, nerve injury, chronic pain, complex regional pain syndrome, implant failure, and fracture healing disorders.

Secondary functional outcome measures included the Patient-Rated Wrist Evaluation score 24 and the visual analogue scale score. 25 Secondary clinical outcome measures included grip strength, range of wrist extension (in degrees), range of wrist flexion (in degrees), range of wrist pronation (in degrees), range of wrist supination (in degrees), radial deviation (in degrees), and ulnar deviation (in degrees). Secondary radiologic outcome measures included volar tilt (in degrees), radial inclination (in degrees), radial height (in millimeters), articular step-off (in millimeters), and ulnar variance (in millimeters).

Data were analyzed in September 2019. Continuous variables are presented as means with SDs or ranges. Continuous variables were converted to mean (SD) if sufficient information was available, using the methods described in the Cochrane Handbook for Systematic Reviews of Interventions. 26 Dichotomous variables were extracted as absolute number and percentage. Dichotomous outcomes were pooled using the Mantel-Haenszel method and presented as risk ratios (RRs) with 95% CIs. Continuous outcomes were pooled using the inverse variance weighting method and presented as mean differences (MDs) with 95% CIs. 26 All analyses were performed using random-effects models. Statistical heterogeneity between studies was assessed by visual inspection of forest plots and by the I 2 and χ 2 statistics for heterogeneity. The significance level for treatment effects was determined by the overall-effect z test. All analyses were performed stratified by study design (RCT or observational study). Differences in effect estimates between the 2 subgroups were assessed, as described in the Cochrane Handbook for Systematic Reviews of Interventions. 26 The significance level for difference in effect estimates across the subgroups was determined by the test for subgroup differences. The significance level for treatment effects and differences across the subgroups was defined as 2-sided P  < .05. Potential publication bias was assessed by visual inspection of funnel plots with MD or RR and standard error and Egger statistical tests. 27 , 28 Statistical meta-analyses were performed using Review Manager (RevMan, version 5.3.5). 29 Additional random-effects meta-regression analyses and Egger statistical tests for publication bias were performed in R, version 3.6.1 (R Project for Statistical Computing). 30

Subgroup analyses were performed for the primary outcome measures, the medium-term DASH score and complication rate, by stratifying by studies that only included patients 60 years or older and the other studies that included patients 18 years or older. In addition, random-effects meta-regression was performed, in which the reported mean difference in medium-term DASH score was regressed according to the mean age of the different study populations. Secondary subgroup analyses were performed including only high-quality studies and according to year of the study period. High-quality studies were defined as having a MINORS score of 16 or higher. The subgroup analyses for study period were performed with studies that included patients after 2008 to account for the development of new operative techniques and nonoperative treatment modalities during the past decade.

A flowchart of the literature search and study selection is shown in eFigure 1 in the Supplement . In total, 23 unique studies were included in this systematic review and meta-analysis, including 8 RCTs and 15 observational studies. 31 - 53

The 23 studies included 2254 unique patients, of whom 1040 were treated operatively and 1214 nonoperatively. The overall weighted mean age was 67 (range, 22-90) years (66 years in the operative group and 67 years in the nonoperative group). Overall, the studies that presented sex data included 425 men (19.4%) and 1769 women (80.6%). The overall follow-up ranged from 6 to 156 months. The baseline characteristics for RCTs and observational studies are presented in Table 1 . In addition, eTable 3 in the Supplement presents the treatment and fracture characteristics of all included studies. The studies included 851 patients (37.8%) who sustained an AO fracture type A; 164 (7.3%), type B; 689 (30.6%), type C; and 550 (24.4%), unknown type.

The 8 RCTs 31 , 35 , 36 , 38 , 46 - 49 included 656 patients (29.1%), of whom 322 were treated operatively and 334 nonoperatively. The weighted mean age was 67 years (67 years in the operative group and 68 years in the nonoperative group). The studies included 130 men (19.8%). The operative method was open reduction and internal fixation with a volar plate in 6 studies, 35 , 38 , 46 - 49 external fixation in 1 study, 31 and percutaneous pinning in 1 study. 36 The conservative method was cast immobilization in all studies.

The 15 observational studies (3 prospective 39 , 41 , 44 and 12 retrospective 32 - 34 , 37 , 40 , 42 , 43 , 45 , 50 - 53 cohort studies) included 1598 patients (70.9%). Operative treatment was performed in 718 patients (44.9%), and 880 (55.1%) were treated nonoperatively. The weighted mean age in the studies was 67 years (66 years in the operative group and 67 years in the nonoperative group). The studies that presented sex data included 295 men (19.2%). The operative method was open reduction and internal fixation with a volar plate in 6 studies, 34 , 39 , 41 , 42 , 51 , 53 external fixation in 1 study, 32 percutaneous pinning in 1 study, 33 intramedullary nail fixation in 1 study, 50 k-wire fixation in 1 study, 43 and unclear or a combination of methods in 5 studies. 37 , 40 , 44 , 45 , 52 The conservative method was cast immobilization in 13 studies 32 , 34 , 37 , 39 - 45 , 50 , 51 , 53 and unclear in 2 studies. 33 , 52

The overall mean MINORS score was 17.2 (SD, 3.6; range, 11-23). The mean MINORS score for the RCTs was 20.9 (SD, 2.0; range, 17-23). The mean MINORS score for the observational studies was 15.2 (SD, 2.5; range, 11-20). The details and distribution of MINORS scores are provided in eTable 4 in the Supplement .

Medium-term (≤1 year) functional outcome assessed according to the DASH score was reported in 10 studies, including 4 RCTs 35 , 38 , 47 , 48 and 6 observational studies, 39 - 41 , 44 , 50 , 51 with 845 patients. The AO fracture type was known for 716 patients. Of these, 402 patients (56.1%) sustained an AO fracture type A; 55 (7.7%), type B; and 259 (36.2%), type C. The overall pooled effect revealed that operative treatment was associated with a significant improvement in the medium-term DASH score compared with nonoperative treatment (MD, −5.22 [95% CI, −8.87 to −1.57]; P  = .005; I 2  = 84%) ( Figure 1 ). There was no difference in effect estimates from RCTs compared with observational studies (test for subgroup differences, χ 2 1  = 0.008; P  = .78). There was no visual asymmetry in the funnel plot (eFigure 2 in the Supplement ). The Egger linear regression test (slope, 1.51; t  = 1.61; P  = .15) indicated no evidence of publication bias.

Complication rate was reported in 19 studies, including 8 RCTs 31 , 35 , 36 , 38 , 46 - 49 and 11 observational studies. 32 - 34 , 37 , 39 - 42 , 45 , 50 , 51 The overall pooled effect showed no difference in complication rate between operative and nonoperative treatment with an RR of 1.03 (95% CI, 0.69-1.55; P  = .87; I 2  = 62%) ( Figure 2 ). No difference was found in effect estimates from RCTs compared with observational studies (test for subgroup differences, χ 2 1  = 0.05; P  = .83). There was no visual asymmetry in the funnel plot (eFigure 3 in the Supplement ). The Egger linear regression test (slope, 1.11; t  = 0.02; P  = .99) indicated no evidence of publication bias. The incidence of complications was 18.8% (147 of 784) after operative treatment compared with 17.1% (147 of 861) after nonoperative treatment. Complication classification and incidence are presented in Table 2 . The main complications after operative treatment were nerve injury or symptoms (26 of 784 [3.3%]) and infection (25 of 784 [3.2%]). The main complications after nonoperative treatment were nerve injury or symptoms (57 of 861 [6.6%]) and chronic pain or complex regional pain syndrome (33 of 861 [3.8%]).

No difference was found regarding the secondary functional outcome measures (eFigures 4-8 in the Supplement ). Descriptive details on functional outcome measures are provided in eTable 5 in the Supplement .

Grip strength was reported in 13 studies, including 6 RCTs 35 , 36 , 46 - 49 and 7 observational studies, 33 , 34 , 39 , 40 , 50 , 51 , 53 and was assessed in kilograms (509 patients) and percentage of the unaffected side (462 patients). Both methods revealed an improvement of the grip strength in favor of operative treatment in grip strength measured in kilograms (MD, 2.73 [95% CI, 0.15-5.32]; P  = .04; I 2  = 79%) and grip strength as a percentage of the unaffected side (MD, 8.21 [95% CI, 2.26-14.15]; P  = .007; I 2  = 76%) (eFigures 9 and 10 in the Supplement ).

There was no difference regarding range of wrist extension, range of wrist flexion, range of wrist pronation, range of wrist supination, radial deviation, and ulnar deviation (eFigures 11-16 in the Supplement ). Descriptive details on clinical outcome measures are provided in eTables 6 and 7 in the Supplement .

There was a significant improvement in favor of operative treatment regarding volar tilt (MD, 5.49° [95% CI, 2.94°-8.03°]; P  < .001; I 2  = 90%), radial inclination (MD, 3.46° [95% CI, 2.73°-4.18°]; P  = .001; I 2  = 54%), radial height (MD, 2.36 [95% CI, 1.87-2.85] mm; P  < .001; I 2  = 54%), and articular step-off (MD, −0.27 [95% CI, −0.51 to –0.03] mm; P  = .03; I 2  = 83%) (eFigures 17-20 in the Supplement ). There was no difference between treatment groups regarding the ulnar variance (MD, −0.29 [95% CI, −0.97 to 0.40] mm; P  = .41; I 2  = 92%) (eFigure 21 in the Supplement ). Descriptive details on radiologic outcome measures are provided in eTable 8 in the Supplement .

The results of the subgroup analyses are presented in Table 3 . The medium-term DASH score for studies that only included patients 60 years or older was reported in 4 studies (2 RCTs 35 , 38 and 2 observational studies 39 , 40 ), with 387 patients and an overall mean age of 75 years. These studies included 247 patients (63.8%) who sustained an AO fracture type A; 9 (2.3%), type B; and 131 (33.9%), type C. The overall pooled effect showed no difference in the medium-term DASH score (MD, −0.98 [95% CI, −3.52 to 1.57]; P  = .45; I 2  = 34%) (eFigure 22 in the Supplement ). The medium-term DASH score for other studies that included patients 18 years or older was reported in 6 studies (2 RCTs 47 , 48 and 4 observational studies 41 , 44 , 50 , 51 ), with 458 patients and an overall mean age of 59 years. The AO fracture type was known for 329 patients, including 155 (47.1%) who sustained an AO fracture type A; 46 (14.0%), type B; and 128 (38.9%), type C. The overall pooled effect revealed operative treatment was associated with a significant improvement of the medium-term DASH score compared with nonoperative treatment (MD, −7.50 [95% CI, −12.40 to −2.60]; P  = .003; I 2  = 77%) (eFigure 22 in the Supplement ). There was a significant difference in effect estimates from studies that only included patients 60 years or older compared with the other studies that included patients 18 years or older (test for subgroup differences, χ 2 1  = 5.37; P  = .02) (eFigure 22 in the Supplement ).

Results of the random-effects meta-regression analysis are shown in Figure 3 ; the trend of the MD in medium-term DASH score appears to decrease by 0.28 per year increase in the mean age of the study population (estimated regression coefficient, 0.28 [95% CI, −0.03 to 0.59]; P  = .07). In the studies that only included patients 60 years or older, there was a significant difference in complication rate in favor of nonoperative treatment (RR, 1.51 [95% CI, 1.15-2.00]; P  = .003; I 2  = 0%), compared with other studies that included patients 18 years or older (RR, 0.73 [95% CI, 0.39-1.38]; P  = .34; I 2  = 60%) (test for subgroup differences: P  = .04) (eFigure 23 in the Supplement ). The results of all the secondary subgroup analyses are presented in Table 3 and eFigures 24 to 27 in the Supplement .

Operative treatment of distal radius fractures was associated with an improvement in medium-term DASH score compared with nonoperative treatment in adults. No difference was observed in complication rate between treatment groups. There was also an improvement of grip strength in favor of operative treatment. However, no difference was found in medium-term DASH score in the subgroup of studies that only included patients 60 years or older. Furthermore, in the studies that only included these patients, a significant difference in complication rate favored nonoperative treatment. Subgroup analyses with high-quality studies and studies with a study period after 2008 showed similar results, compared with the primary analyses. No difference was found between effect estimates from RCTs and observational studies regarding the primary outcome measures (medium-term DASH score and complication rate).

The pooled effect estimates showed that operative treatment was associated with an improvement in medium-term DASH score compared with nonoperative treatment, which is in contrast to findings of previous meta-analyses. 3 - 5 Song et al 3 pooled functional outcome according to the medium-term DASH score at 12 months from 2 studies with 133 patients and found no difference between treatment groups. Ju et al 4 pooled the DASH score from 6 studies with 577 patients and reported no difference. Chen et al 5 found no difference in DASH score between treatment groups after they evaluated 7 studies with 600 patients. The present review included 10 studies with 845 patients in the medium-term DASH analysis, which resulted in an increased number of patients available for analyses, thus exceeding the samples of previous meta-analyses. Furthermore, only the meta-analysis by Song et al 3 evaluated the DASH score at 12 months. The meta-analyses by Ju et al 4 and Chen et al 5 did not distinguish between medium-term and long-term DASH scores, including the studies by Arora et al 34 and Aktekin et al 32 in their analyses. In the present review, the DASH scores reported by Arora et al 34 and Aktekin et al 32 were used for the evaluation of the long-term DASH score owing to their long-term follow-up periods to 81 months. In general, medium-term functional outcome can be assumed to reflect the effect of treatment, with long-term follow-up being influenced by other conditions, events, or patient factors that in turn could influence functional outcome scores. Reports have shown that the DASH score after distal radius fracture treatment tends to plateau after 12 months. 54 , 55

The previous meta-analyses have mainly focused on elderly patients. Ju et al 4 and Chen et al 5 specifically focused on patient populations 60 years and older. Song et al 3 included only studies with patients 45 years or older, with most of the patients in their DASH analyses 60 years or older. These findings are in accordance with our subgroup analyses of the studies that only included patients 60 years or older, showing no difference in medium-term DASH score. However, we found a significant improvement in medium-term DASH score in the subgroup of other studies that included patients 18 years or older. To our knowledge, with the analyses of 6 studies with 458 patients, this study is the first meta-analysis to evaluate functional outcome focusing on patient populations 18 years or older. The random-effects meta-regression plot confirmed this trend; however, with only 10 studies and based on the mean age of the complete population, the regression is underpowered. Meta-regression is an extension to subgroup analyses that allows the effect of characteristics to be investigated. However, this is rarely possible owing to inadequate numbers of studies, and meta regression should generally not be considered when there are fewer than 10 studies, as described in the Cochrane Handbook for Systematic Reviews of Interventions. 26 This trend shows that, to improve personalized care, further evaluation of individual patient data meta-analyses is needed.

We found no difference in the overall complication rate between operative and nonoperative treatment, in accordance with the studies by Song et al 3 and Yu et al. 56 However, in our analyses with studies that only included patients 60 years or older, a significant difference favored nonoperative treatment. These findings could indicate that operative treatment results in a higher risk of complications in the elderly population. The study by Chen et al 5 subdivided complications into minor and major, classifying minor as not requiring surgical treatment. They found no significant difference in minor complications; however, there was a significant difference in major complications, with the most common major complications being nerve and tendon injuries. In the present review, we did not subdivide major and minor complications; however, we did present complication classifications with incidence, showing that nerve injury or symptoms were the main complications in both groups. In the present review, we were not able to accurately compare major and minor complications or specify nerve injuries and symptoms. Unfortunately, this remains difficult owing to limited or missing information regarding the presentation and treatment of complications in studies.

We found a significant improvement of grip strength in favor of operative treatment, which is in contrast with 2 previous meta-analyses. Ju et al 4 found no significant difference in grip strength in their analysis of 4 studies with 337 patients. Song et al 3 evaluated grip strength at 12 months with the results of 2 studies with 133 patients and found no difference. However, both the meta-analyses by Ju et al 4 and Song et al 3 could be limited by the number of included patients in their grip strength analyses. On the contrary, Chen et al 5 reported grip strength was significantly greater in the operative group in their analyses of 5 studies with 398 patients. In the present review, grip strength was reported in 13 studies and assessed in kilograms and percentage of the unaffected side with 509 and 462 patients, respectively.

We found no significant difference between treatment groups regarding range of wrist motions. These findings are also in accordance with those of Chen et al, 5 who reported wrist range of motion did not differ significantly at final follow-up between the 2 treatment groups.

Subgroup analyses including only high-quality studies or studies performed after 2008 showed similar results regarding the primary outcome measures, medium-term DASH score and complication rate, compared with the primary analyses. Furthermore, no difference was observed in effect estimates from RCTs and observational studies regarding the primary outcome measures. These results are in line with previous orthopedic trauma meta-analyses, 9 - 12 including RCTs and observational studies, showing high-quality observational studies to result in similar treatment effects compared with RCTs. Reports 9 , 11 - 15 , 18 have shown that differences in effect estimates between RCTs and observational studies tend to be small. Randomized clinical trials require strict conditions such as participant selection, inclusion and exclusion criteria, randomization method, and outcome measurements. Patient population in daily clinical practice might differ from the often highly selected patient populations in RCTs. 57 - 59 The results of observational studies, representing daily clinical practice with various levels of surgical experience and differences in operative techniques, could complement those of RCTs, provided that confounding has been adequately addressed. 17 , 18 Including observational studies in meta-analyses that evaluate surgical interventions increases sample size and may facilitate subgroup analysis. These results could help to understand the generalizability of previous results and improve existing guidelines.

Operative treatment of distal radius fractures results in a significant improvement of the medium-term DASH score and grip strength in adults, with no significant difference in overall complication rate. These results might support the international increase of operative treatment of distal radius fractures. 6 Operative treatment might be the preferred treatment for distal radius fractures in younger patients. However, patient- and fracture-specific factors (patient preference, handedness, occupation, comorbidities, fracture displacement, etc) should always be taken into consideration, and patients should be counseled regarding incidence of complications. Studies have shown an increase of distal radius fractures in patients aged 17 to 64 years. 2 Hence, future studies should also focus on the nonelderly population, because traditionally most studies on this topic solely include patient populations 60 years or older. Further investigation is warranted to understand the optimal treatment methods and outcomes in this nonelderly, generally healthy, and still working age group. Furthermore, for the evaluation of the effect on the health and well-being of nonelderly adults, future studies could also focus on return to sporting activity and return to work, aside from traditional outcomes. Unfortunately, comparison of literature remains difficult owing to a wide variety of AO fracture types, different age groups, operative treatments, the use of different functional outcome measures, and duration of follow-up. Further research is needed for the development of patient- and fracture-specific guidelines.

Potential limitations in this review need to be acknowledged. First, analyses could be influenced by missing results; however, an extensive electronic database search was performed, and funnel plots did not indicate evidence of publication bias. Second, the subgroup analyses regarding age were stratified based on the inclusion criteria of studies, which resulted in overlap of the age distributions between the subgroup analyses. Nevertheless, there still was a substantial difference in the overall mean age in both subgroups (59 years vs 75 years). Furthermore, it should be noted that the cutoff of 60 years or older is arbitrarily chosen to compare our findings with the previous meta-analyses that mainly focused on patient populations 60 years and older. We acknowledge that better evidence is lacking, and further evaluation using individual patient data meta-analysis is needed. Third, we were not able to accurately classify all complications. Unfortunately, this remains difficult owing to insufficient or missing information. In addition, this review included a variety of fracture types. The AO fracture types A, B, and C seemed equally distributed throughout the different functional outcome analyses, with most studies including AO types A and C fractures. However, reports have shown patient-reported outcomes to vary in the setting of multiple-trauma or high-energy injury mechanisms. In addition to demographic and fracture characteristics, factors related to injury context (multiple-trauma, high-energy mechanism) could also account for differences in patient-reported wrist function after distal radius fractures. 60 , 61

This meta-analysis found that operative treatment of distal radius fractures improved the medium-term DASH score and grip strength compared with nonoperative treatment in adults. There was no difference in complication rate between treatment groups. However, there was no difference in medium-term DASH score in the subgroup of studies that only included patients 60 years or older. Furthermore, in this subgroup, operative treatment resulted in a significantly higher complication rate. Our findings suggest that operative treatment might be more effective and have a greater effect on the health and well-being of younger, nonelderly patients. However, to improve personalized care, this trend needs to be confirmed with patient-level data. Further evaluation of individual patient data meta-analyses is needed.

Accepted for Publication: February 21, 2020.

Published: April 23, 2020. doi:10.1001/jamanetworkopen.2020.3497

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2020 Ochen Y et al. JAMA Network Open .

Corresponding Author: Yassine Ochen, MD, Department of Orthopedic Surgery, Harvard Medical School Orthopedic Trauma Initiative, Massachusetts General Hospital, Boston, 55 Fruit St, Yawkey 3960, Boston, MA, 02114 ( [email protected] ).

Author Contributions: Dr Ochen had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: Ochen, Peek, Beeres, van Heijl, Groenwold, Heng.

Drafting of the manuscript: Ochen, Peek, Beeres, Houwert.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Ochen, Peek, Groenwold.

Administrative, technical, or material support: Heng.

Supervision: van der Velde, Beeres, van Heijl, Houwert, Heng.

Conflict of Interest Disclosures: None reported.

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Peer-reviewed

Research Article

The cost-effectiveness of preventing, diagnosing, and treating postpartum haemorrhage: A systematic review of economic evaluations

Roles Conceptualization, Data curation, Formal analysis, Project administration, Visualization, Writing – original draft, Writing – review & editing

Affiliation Maternal, Child and Adolescent Health Program, Burnet Institute, Melbourne, Australia

Roles Data curation, Formal analysis

Affiliations Maternal, Child and Adolescent Health Program, Burnet Institute, Melbourne, Australia, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia

Roles Data curation

Affiliation Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia

Roles Conceptualization, Data curation, Writing – review & editing

Roles Writing – review & editing

Roles Conceptualization, Project administration, Supervision, Writing – review & editing

* E-mail: [email protected]

• Joshua F. Ginnane, 
• Samia Aziz, 
• Saima Sultana, 
• Connor Luke Allen, 
• Annie McDougall, 
• Katherine E. Eddy, 
• Nick Scott, 
• Joshua P. Vogel

• Published: September 13, 2024
• https://doi.org/10.1371/journal.pmed.1004461
• Peer Review
• Reader Comments

This is an uncorrected proof.

Postpartum haemorrhage (PPH) is an obstetric emergency. While PPH-related deaths are relatively rare in high-resource settings, PPH continues to be the leading cause of maternal mortality in limited-resource settings. We undertook a systematic review to identify, assess, and synthesise cost-effectiveness evidence on postpartum interventions to prevent, diagnose, or treat PPH.

Methods and findings

This systematic review was prospectively registered on PROSPERO (CRD42023438424). We searched Medline, Embase, NHS Economic Evaluation Database (NHS EED), EconLit, CINAHL, Emcare, Web of Science, and Global Index Medicus between 22 June 2023 and 11 July 2024 with no date or language limitations. Full economic evaluations of any postpartum intervention for prevention, detection, or management of PPH were eligible. Study screening, data extraction, and quality assessments (using the CHEC-E tool) were undertaken independently by at least 2 reviewers. We developed narrative syntheses of available evidence for each intervention.

From 3,993 citations, 56 studies were included: 33 studies of preventative interventions, 1 study assessed a diagnostic method, 17 studies of treatment interventions, 1 study comparing prevention and treatment, and 4 studies assessed care bundles. Twenty-four studies were conducted in high-income countries, 22 in upper or lower middle-income countries, 3 in low-income countries, and 7 studies involved countries of multiple income levels. Study settings, methods, and findings varied considerably. Interventions with the most consistent findings were the use of tranexamic acid for PPH treatment and using care bundles. In both cases, multiple studies predicted these interventions would either result in better health outcomes and cost savings, or better health outcomes at acceptable costs. Limitations for this review include that no ideal setting was chosen, and therefore, a transferability assessment was not undertaken. In addition, some sources of study uncertainty, such as effectiveness parameters, were interrogated to a greater degree than other sources of uncertainty.

Conclusions

In this systematic review, we extracted, critically appraised, and summarised the cost-effectiveness evidence from 56 studies across 16 different interventions for the prevention, diagnosis, and treatment of PPH. Both the use of tranexamic acid as part of PPH treatment, and the use of comprehensive PPH bundles for prevention, diagnosis, and treatment have supportive cost-effectiveness evidence across a range of settings. More studies utilizing best practice principles are required to make stronger conclusions on which interventions provide the best value. Several high-priority interventions recommended by World Health Organization (WHO) such as administering additional uterotonics, non-pneumatic anti-shock garment, or uterine balloon tamponade (UBT) for PPH management require robust economic evaluations across high-, middle-, and low-resource settings.

Author summary

Why was this study done.

• There are wide array of interventions available to prevent, diagnose, and treat postpartum haemorrhage (PPH).
• The decision on which interventions governments should invest in is challenging, particularly when resources are scarce.
• Systematic reviews on the cost-effectiveness of interventions can assist this decision-making process by providing clear comparisons between options.

What did the researchers do and find?

• This is, to our knowledge, the first systematic review of economic evaluations covering prevention, diagnosis, and treatment of PPH.
• We identified 56 relevant studies across 16 interventions and summarised the findings from these studies in a comparable way.
• We found consistent evidence that adding tranexamic acid to PPH treatment, and the use of comprehensive care bundles combining preventative, diagnostic, and treatment interventions, are cost-effective.

What do these findings mean?

• The use of tranexamic acid for PPH treatment has been shown to be either cost-saving or highly cost-effective across multiple settings.
• The combination of multiple interventions into a care bundle is promising—available data suggests these approaches can be cost-effective.
• Sixteen World Health Organization (WHO) recommendations on the prevention, identification of treatment of PPH do not yet have robust cost-effectiveness evidence.
• Study limitations include that no ideal setting was chosen to compare interventions in, and that some sources of study uncertainty were interrogated to a greater extent than others.

Citation: Ginnane JF, Aziz S, Sultana S, Allen CL, McDougall A, Eddy KE, et al. (2024) The cost-effectiveness of preventing, diagnosing, and treating postpartum haemorrhage: A systematic review of economic evaluations. PLoS Med 21(9): e1004461. https://doi.org/10.1371/journal.pmed.1004461

Academic Editor: Andrew Shennan, King’s College, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND

Received: April 23, 2024; Accepted: August 14, 2024; Published: September 13, 2024

Copyright: © 2024 Ginnane et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting information files.

Funding: J.F.G. received a Shark Tank Grant from the Burnet Institute, Melbourne (no grant number available) for this review. J.P.V. is supported by an Australian National Health and Medical Research Council Emerging Leadership Investigator Grant (GNT1194248). Funders played no role in the study design, data collection, analysis, narrative synthesis or writing of this review.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations: CCEMG, Campbell and Cochrane Economics Methods Group; DALY, disability-adjusted life year; GDP, gross domestic product; LMIC, low- and middle-income country; MMR, maternal mortality ratio; NASG, non-pneumatic anti-shock garment; PCVT, point-of-care viscoelastic testing; PPH, postpartum haemorrhage; PPP, purchasing power parity; PSA, probabilistic sensitivity analysis; TBA, traditional birth attendant; UBT, uterine balloon tamponade; VHW, village health worker; WHO, World Health Organization

Introduction

Postpartum haemorrhage (PPH) is a time-critical obstetric emergency, defined by the World Health Organization (WHO) as postpartum blood loss of more than 500 ml, regardless of mode of birth [ 1 ]. PPH affects approximately 6% of women giving birth and is the most common direct cause of maternal mortality, responsible for an estimated 19.7% of maternal deaths [ 2 , 3 ]. The incidence and resulting maternal mortality caused by PPH are disproportionately concentrated in low- and middle-income countries (LMICs) [ 4 ]. In addition to the health considerations, PPH also burdens health systems financially. Births complicated by PPH incur costs 21% to 309% higher than births without complications in LMICs [ 5 ]. Since 2015, progress on reducing the global maternal mortality ratio (MMR) appears to have stalled. It seems increasingly unlikely that the Sustainable Development Goals target 3.1—to reduce the global MMR to less than 70 per 100,000 live births by 2030—will be met [ 4 , 6 ]. The 2020 MMR estimates indicate that 223 maternal deaths occur per 100,000 live births worldwide [ 6 ]. Renewed efforts are required to address the underlying drivers of preventable pregnancy-related deaths, including the most common cause, PPH.

Deaths from PPH have largely been eliminated in high-income countries, due to coordinated interventions aimed at preventing, detecting, and treating PPH [ 4 ]. Preventative interventions include the use of prophylactic uterotonics such as oxytocin, carbetocin, ergometrine/methylergometrine, or misoprostol for all women immediately after birth. Alongside uterotonics, tranexamic acid can also be administered to further reduce the risk of excessive blood loss and the requirement for blood transfusion [ 7 ]. To diagnose PPH promptly, assessment of uterine tone and the measurement of blood loss postdelivery is recommended. Blood loss is either visually estimated or measured through collecting blood in a calibrated drape, weighing blood-soaked materials or the use of more sophisticated colorimetric systems [ 8 , 9 ]. If PPH occurs despite preventative measures, treatment should be commenced as soon as possible—this includes uterine massage, additional uterotonics, tranexamic acid, and intravenous fluids. If bleeding continues (i.e., refractory PPH), the use of devices such as uterine balloon tamponade (UBT) or a non-pneumatic antishock garment, compressive measures, and the administration of blood products may be required [ 10 ]. More invasive interventions may be required if bleeding continues. These include surgical treatments such as uterine compression sutures, uterine artery ligation or embolization, or hysterectomy [ 10 ]. At the health system level, implementing PPH-related care protocols, as well as ensuring adequate training and supervision for health workers, is key to ending PPH-related morbidity and mortality.

Considering the cost-effectiveness of interventions for PPH prevention, detection, and treatment is important for 2 reasons. Firstly, PPH disproportionately affects women in LMICs—in these countries, financial pressures on the health system mean that difficult decisions are taken around what interventions can be offered [ 4 ]. Cost-effectiveness analyses are therefore especially useful to national decision-makers to ensure optimal health impacts for available budget. Secondly, the 2023 WHO Roadmap to Combat Postpartum Haemorrhage has foreshadowed new consolidated WHO PPH guidelines [ 4 ]. Developing these guidelines involves explicit consideration of economic evidence, to assess the cost-effectiveness and resource requirements of candidate interventions. Previous systematic reviews on the cost-effectiveness of PPH interventions have solely focussed on the use of uterotonics for PPH prevention [ 11 ], or the use of UBT [ 12 ] or tranexamic acid for PPH treatment [ 13 ]. This systematic review thus aimed to broaden the evidence available from previous reviews by identifying, assessing, and synthesising all available evidence from economic evaluations of any postpartum intervention for PPH prevention, diagnosis, or treatment.

For this review, we followed guidelines from the Expert Review of Pharmacoeconomics and Outcomes Research [ 14 ] and reported findings in line with the Preferred Reporting Items for Systematic reviews and Meta-analyses (PRISMA) 2020 statement (Table A in S1 Appendix ) [ 15 ]. We prospectively registered the review protocol on PROSPERO (CRD42023438424). All included articles have been previously published, and ethics approval was not required.

Eligibility criteria

Full economic studies that have evaluated the cost-effectiveness, cost-utility, or cost-benefit of any method of PPH prevention, diagnosis, or treatment delivered in the postpartum period (from time of birth until 42 days postpartum) were included. We defined full economic evaluations as any evaluation that considered both health consequences and cost consequences of an intervention against a comparator in the single analysis. We considered any such intervention to be eligible, regardless of its effectiveness, or whether it is recommended by WHO or not. Effectiveness studies that included a full economic evaluation such as randomised trials, non-randomised interventional studies, or observational studies (cohort, case-control, cross sectional designs) were also eligible. Partial economic evaluations—those which did not consider both economic and health outcomes compared to a comparator—were excluded. Conference abstracts, protocols, grey literature, and reviews of existing evidence were excluded. There were no limitations based on date or language.

Information sources, search strategy, and selection process

The search strategy was developed with an expert librarian and run on Medline, Embase, NHS Economic Evaluation Database, EconLit, CINAHL, Emcare, Web of Science, and Global Index Medicus ( S2 Appendix ). A scoping review of 923 economic evaluations of maternal health interventions was also searched for relevant articles [ 16 ]. Resulting citations were uploaded into Covidence software where at least 2 authors (JFG, SA, SS, CA, KE, MDS) independently screened citations by title/abstract level. Full texts of potentially eligible studies were reviewed by 2 reviewers (JFG, SA, SS, CA, KE, MDS). We recorded reasons for exclusion of any full texts. Disputes were resolved through discussion or input from other reviewers.

Data extraction, synthesis, and quality assessment

Data from each included study was extracted by 2 authors independently into pre-tabulated Excel spreadsheets adapted from previous reviews (Table A in S3 Appendix ) [ 13 , 16 , 17 ]. One study was only available in Chinese. It was translated for extraction using Google Translate, and the translation confirmed by a native speaking colleague.

Cost-effectiveness analysis is highly dependent on the effectiveness estimate used; the accuracy of these estimates is thus a possible source of bias [ 18 ]. For each study, we extracted the effectiveness data used and compared it to an up-to-date effectiveness estimate from the corresponding WHO recommendation and systematic reviews of that intervention. When an included study based its cost-effectiveness calculations on an effectiveness estimate that differed significantly (outside of 95% confidence intervals) from an effectiveness estimate found in the literature, we flagged this as at risk of bias.

Costs were extracted unadjusted, in the year and currency stated by the study. For ease of comparison, all costs were converted to 2023 United States Dollars (USD) using an online tool developed by the Campbell and Cochrane Economics Methods Group (CCEMG) and the Evidence for Policy and Practice Information and Coordinating Centre (EPPI-Centre) [ 19 ]. This tool completes a two-stage cost conversion, first adjusting for the cost-year using a gross domestic product (GDP) deflator index, and then a currency conversion using purchasing power parities (PPPs) for GDP [ 20 ]. Quality assessments of included studies were completed independently by 2 reviewers (JFG, SA, SS) using the Consensus on Health Economics Criteria extended list (CHEC-E; Table A in S4 Appendix ) as this is suitable to evaluate economic evaluations based on clinical trials or modelling studies [ 14 , 21 , 22 ]. Studies scoring 0% to 49% were considered “low quality,” 50% to 74% as “moderate quality,” and >75% as “high quality.” Disagreements on data extraction or CHEC-E assessment were resolved through discussion or consulting other reviewers.

Studies were grouped for analysis by the characteristics and goal of the intervention, namely PPH prevention, diagnosis, or treatment. Due to heterogeneity of study designs within and between interventions, a narrative synthesis approach was used. A transferability assessment was not completed as no ideal setting was selected to compare to. To identify evidence gaps, we mapped included studies to current WHO recommendations. All guidance from the WHO recommendations for the prevention and treatment of PPH from 2012 were reviewed [ 1 ], in addition to the various individual updates that WHO have published to these recommendations up until the end of 2023 [ 23 – 29 ].

Characteristics of included studies

Searches identified 3,993 citations, of which, 56 were eligible for inclusion ( Fig 1 ; see Table A in S5 Appendix for excluded studies). Two additional citations were identified after reference review. Of the 58 total eligible citations, 2 (2/58) were found to be additional publications from the same studies meaning only 56 unique studies were identified. Of the included studies, 33 (33/56) assessed PPH prevention interventions, 1 (1/56) assessed prevention versus treatment, 1 (1/56) assessed a diagnostic method alone, 17 (17/56) assessed PPH treatments, and 4 (4/56) assessed combinations (bundles) of prevention and treatment, or diagnosis and treatment ( Fig 2 ). Studies were published between 2006 and 2024 and were conducted in low-income (3/56), lower-middle income (14/56), upper-middle income (8/56), and high-income (24/56) countries. Seven (7/56) studies were completed across multiple income level settings. Thirty-four studies (34/56) were set in hospitals, 13 (13/56) studies assessed interventions across multiple settings, 3 (3/56) studies assessed interventions for home births, 2 (2/56) studies assessed an intervention at a primary health setting, and 4 (4/56) studies did not clearly define which health facilities the studies were set. Of the 56 economic evaluations, 38 (38/56) were models, and 18 (18/56) were part of effectiveness trials. Study characteristics are summarised in Table 1 , including the perspective, time horizon, and overall CHEC-E score for each study. Most studies were conducted and reported comprehensively, with 33 (33/56) studies assessed as high quality on CHEC-E, 12 (12/56) moderate, and 11 (11/56) low (detailed study characteristics are presented in Table A in S6 Appendix and full CHEC-E assessments in Tables A–D in S7 Appendix ). S8 Appendix provides comparisons of effectiveness data used in each economic analysis, against estimates from published effectiveness reviews. Economic studies on interventions that are recommended by WHO (29 recommendations) were mapped to each recommendation by study country and country income level ( S9 Appendix ). For 16 (16/29) WHO recommended interventions, we identified zero economic evaluations. For 1 (1/29) recommendation, we identified studies from high-income countries only, and for 12 (12/29) recommendations, we identified corresponding studies from a range of high-, middle-, or low-income countries.

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https://doi.org/10.1371/journal.pmed.1004461.g001

The top half of this figure represents the timing and order of commonly utilised preventative, diagnostic, and treatment interventions for postpartum haemorrhage. The bottom half of this figure displays the types of interventions assessed in the 56 studies we identified. *Not a WHO recommended intervention. # One study is listed twice as it included assessments of both uterotonics for prevention and uterotonics for PPH treatment. Number of studies identified per intervention type is shown in parenthesise. GTN, glyceryl trinitrate; IV, intravenous; NASG, non-pneumatic anti-shock garment; NIPD, negative intrauterine pressure device; PPH, postpartum haemorrhage; WHO, World Health Organization.

https://doi.org/10.1371/journal.pmed.1004461.g002

https://doi.org/10.1371/journal.pmed.1004461.t001

The results are discussed by intervention type in the text and tables below but can also be viewed by study region and country ( S10 Appendix ).

Economic evaluations of preventative interventions

Prophylactic uterotonics..

Twenty-six (26/56) studies focused on preventative uterotonics ( Table 2 ). A high-quality health technology assessment considered cost-effectiveness of uterotonics for PPH prevention in United Kingdom (UK) hospitals in 2019 [ 30 , 31 ]. For vaginal birth, carbetocin was the most effective—incurring an incremental $1,530.93 per extra PPH > 500 ml averted when switching from oxytocin. For cesarean section, carbetocin was the second most effective and least costly, while misoprostol plus oxytocin was the most effective. This meant that switching from carbetocin to misoprostol plus oxytocin for cesarean section would incur an additional $4,091.60 per case of PPH ≥ 500 ml avoided. Mixed findings across analyses and a degree of uncertainty in the results led the authors to recommend against changing current practice (oxytocin for all births).

https://doi.org/10.1371/journal.pmed.1004461.t002

Five studies used decision analytic models to compare carbetocin with oxytocin for both vaginal birth and cesarean section [ 32 – 36 ]. Models set in Canadian [ 35 ], and Chinese hospitals [ 34 ], and Indian primary, secondary, and tertiary health facilities [ 32 ] found that implementing carbetocin was dominant (both cost-saving and more efficacious) compared with oxytocin or misoprostol. A Colombian study concluded carbetocin would be either cost saving or cost-effective for cesarean section but not for vaginal birth [ 33 ]. A study in the Philippines found carbetocin was not cost-effective for either mode of birth [ 36 ]. However, three of these models [ 33 , 35 , 36 ] used effect estimates that may have either under- [ 33 , 36 ] or over-estimated [ 33 , 35 ] the relative effectiveness of carbetocin [ 30 , 37 , 38 ] (Table O in S8 Appendix ). The 2 studies using effect estimates consistent with current evidence both found carbetocin to be dominant [ 32 , 34 ].

Seven studies, including 3 evaluations from effectiveness studies [ 39 – 41 ] and 4 models [ 42 – 45 ], assessed carbetocin against oxytocin for cesarean section only. Five concluded that carbetocin was the favourable option being either dominant, in the UK [ 41 , 44 ] and Australia [ 40 ], or cost-effective in Peru [ 42 ] and Ecuador [ 43 ]. Two of these studies (including 1 assessed as low quality) [ 41 ] may have over-estimated the relative effectiveness of carbetocin [ 41 , 42 ] (Table O in S8 Appendix ). A Malaysian study concluded carbetocin was more effective but more costly for cesarean section [ 45 ] and did not state a cost-effectiveness threshold to interpret this finding. In contrast, one study concluded that oxytocin was the favourable option for the UK [ 39 ], although this study was low quality and used effectiveness data that may underestimate the effectiveness of carbetocin [ 39 ] (Table O in S8 Appendix ). For vaginal birth, one UK study compared carbetocin and oxytocin in hospitals, concluding carbetocin was likely to be dominant [ 46 ]. The study was high quality, and the effectiveness estimates used in the model were consistent with recent systematic reviews.

Five studies assessed oxytocin compared to no uterotonics, non-injectable uterotonics, or other formulations of oxytocin [ 47 – 51 ]. Heterogeneity in their settings, quality and completeness of methods, prevented meaningful comparisons between studies. One of the studies was on an inhalable form of oxytocin still under investigation, and the other 4 studies were each based on effectiveness estimates inconsistent with more recent evidence. For completeness, the results of each of these studies are summarised in S11 Appendix ; however, the most complete assessment of the cost-effectiveness of oxytocin appear as part of the UK health technology assessment from 2019 discussed earlier [ 30 , 31 ].

Six modelling studies analysed cost-effectiveness of misoprostol [ 52 – 57 ]. An Indian study assessed preventative misoprostol administered by village health workers (VHW) during home births compared to no uterotonics. They reported this strategy could reduce maternal deaths by 38% and cost $1,812.44 per death averted [ 56 ]. Another comparing misoprostol as prevention or treatment to no uterotonics found preventative misoprostol was the most effective strategy, incurring $218.26 per disability-adjusted life year (DALY) averted compared with misoprostol as treatment [ 57 ]. A third Indian study considered adding community-based distribution of misoprostol to other service and infrastructure upgrades [ 52 ]. The estimated maternal mortality reduction compared to other upgrades alone was modest (6.9% to 12.3%), but estimated to be cost-saving over a lifetime horizon [ 52 ]. These 3 studies assumed misoprostol to be significantly more effective than indicated in systematic reviews (Table O in S8 Appendix ) and may therefore overestimate its cost-effectiveness [ 30 , 37 ].

In other settings, a Ugandan study estimated advanced misoprostol distribution would improve health outcomes at small incremental costs from the governmental perspective ($98.80 to $537.91 per DALY averted) or dominate under a societal perspective [ 54 ]. An analysis across sub-Saharan Africa similarly concluded community misoprostol use would incur additional costs and reduce maternal deaths [ 55 ]; they described the strategy as cost-effective without specifying a threshold. The final study assessed community or hospital misoprostol usage in international settings where injectable uterotonics are unavailable [ 53 ]. They concluded that either strategy of utilising misoprostol in the community alone, or in both hospitals and community, would be dominant [ 53 ]. As with the previous misoprostol studies, the underlying effectiveness estimates of all 3 studies was inconsistent with systematic reviews (Table O in S8 Appendix ) [ 30 , 37 ].

A single modelling study analysed active management of the third stage of labour in place of expectant management in Guatemala and Zambia, with an unspecified uterotonic [ 58 ]. In both settings the authors estimated that active management of the third stage of labour would reduce maternal deaths and decrease health facility costs [ 58 ].

Tranexamic acid for prevention.

Three high-quality studies assessed the impact of tranexamic acid for PPH prevention in high-income settings, 1 modelling study in women (vaginal birth or cesarean section) in the United States [ 59 ], and 2 economic evaluations of effectiveness studies in either women undergoing vaginal birth [ 60 ] or cesarean section [ 61 ] in France. In all 3 studies, the tranexamic acid strategy was either deemed cost-effective [ 61 ] or dominant [ 59 , 60 ]; however, there were some differences in the results. In the United States-based model, the impact on cost savings and avoided morbidity were substantial, while in the French studies, there were little differences in the overall effectiveness and costs between tranexamic acid and standard care strategies. The 3 studies scored high on CHEC-E, and 2 were based on effectiveness estimates either consistent [ 59 ] with systematic review estimates [ 7 , 62 , 63 ], or may have underestimated the effectiveness of tranexamic acid [ 60 ], thereby providing conservative cost-effectiveness estimates. The effectiveness estimates in one study were unable to be assessed, as they used a composite effectiveness measure not reported in previous systematic reviews [ 61 ].

Glyceryl trinitrate for prevention.

A health technology assessment completed in UK hospitals evaluated the use of glyceryl trinitrate for the management of retained placenta to reduce the requirement for invasive procedures and the risk of PPH [ 64 , 65 ]. It was not effective at reducing the rate of manual placenta removal, or subsequent PPH, and was therefore not cost-effective [ 64 , 65 ].

Devices for prevention.

One study assessed the cost-effectiveness of using a negative intrauterine pressure suction device alongside active management of the third stage of labour to minimise blood loss and prevent PPH in women following low risk vaginal births in India [ 66 ]. The study reported that using the device resulted in reduced blood loss, reduced rates of PPH (0.49% versus 1.81%, p < 0.001) and reduced hospital expenditure on blood products. Although this study met inclusion criteria for this review, the health economic analysis was extremely limited and only costed blood product usage. In addition, the underlying effectiveness evidence for negative intrauterine pressure devices remains uncertain and large-scale multicentre clinical trials are required [ 66 ].

Surgical practices for prevention.

The remaining 3 evaluations of preventative interventions related to surgical methods for minimising PPH [ 67 – 69 ]. The effectiveness of these interventions is debated. In addition, all 3 scored low on CHEC-E and pertained to a small proportion of women at risk of PPH (those with placenta accreta spectrum and those at high risk of PPH undergoing cesarean section). We therefore summarised their results separately in S12 Appendix .

Economic evaluations of diagnostic interventions

One study in a USA hospital examined the effects of introducing the Triton system—combining colorimetric and gravimetric analysis for quantitative assessment of postpartum blood loss at all births—to improve PPH diagnosis ( Table 3 ) [ 70 ]. Triton implementation increased the proportion of women diagnosed with PPH. They calculated it would result in savings, though the analysis focussed on few types of cost.

https://doi.org/10.1371/journal.pmed.1004461.t003

Economic evaluations of treatment interventions

Medical interventions for pph treatment..

Two studies assessed PPH treatment with misoprostol in settings where other treatment options are limited ( Table 4 ) [ 57 , 71 ]. The first analysed the cost-effectiveness of training traditional birth attendants (TBAs) to recognise and treat PPH with per-rectal misoprostol in sub-Saharan Africa [ 71 ]. They found it could prevent 1,647 cases from progressing to severe PPH, simultaneously saving $160,922 per 10,000 births [ 71 ]. The other study in India assessed a similar strategy of unskilled birth attendants diagnosing and treating PPH with misoprostol [ 57 ]. In this case, the health benefits (not as large as preventative strategies but preferable to no intervention) incurred a low incremental cost of $7.70 per DALY averted [ 57 ]. The studies were moderate [ 57 ] to high [ 71 ] quality. Bias related to treatment effects could not be assessed (Table U in S8 Appendix ).

https://doi.org/10.1371/journal.pmed.1004461.t004

Four modelling evaluations assessed tranexamic acid for PPH treatment—2 in the USA [ 72 , 73 ] and 2 in LMICs (India [ 74 ], Nigeria, and Pakistan [ 75 ]). Both USA studies considered women with PPH following either vaginal birth or cesarean section, concluding that tranexamic acid would likely avert laparotomies, deaths, and reduce healthcare and societal costs, whether on a short-term time horizon [ 73 ] or a lifetime horizon [ 72 ]. The LMIC-based studies were similarly positive for health outcomes but estimated modest incremental costs. These ranged from $86.03 per QALY gained in India [ 74 ] to $239.49 in Nigeria [ 75 ]. All 4 evaluations were high quality, and the effectiveness estimates used were consistent with systematic reviews.

Devices for PPH management.

One evaluation of an effectiveness study [ 76 ] and 1 modelling study [ 77 ] assessed non-pneumatic anti-shock garment (NASG) for women with obstetric haemorrhage in LMICs. One study in Zimbabwe and Zambia compared the cost-effectiveness of applying NASGs to patients in primary health centres awaiting definitive management at a referral centre, to waiting until patients arrived at the referral centre to apply NASG [ 76 ]. Results differed between sites, but on average the costs of distributing and training users of NASG were largely offset by the reduction in other health resources utilised when delaying application. A small incremental cost of $27.64 was incurred for each DALY averted by the intervention [ 76 ]. The second study in Egypt and Nigeria assessed the use of NASG within tertiary hospitals, against routine care without the temporising device [ 77 ]. In Egypt, NASG improved health outcomes and reduced costs, while in Nigeria it improved health outcomes at a modest incremental cost of $3.97 per DALY averted [ 77 ]. These evaluations were moderate [ 76 ] to high [ 77 ] quality. Bias related to treatment effects could not be assessed (Table U in S8 Appendix ).

Two modelling studies assessed the cost-effectiveness of treating PPH with UBT devices in Kenya and India [ 78 , 79 ]. The study in Kenya assessed the “Every Second Matters” (ESM) UBT against standard care either with or without any form of uterine packing [ 79 ]. In this setting, utilising ESM-UBT was considered cost-effective compared to standard care, regardless of whether uterine packing was able to be performed. Incremental costs were between $30.26 and $231.64 per DALY averted, depending on the unit cost and which comparator was chosen [ 79 ]. This model was moderate quality and may be at risk of bias related to treatment effects (Table U in S8 Appendix ). The Indian study compared the relative cost-effectiveness between 3 UBT models—the ESM-UBT, the Bakri-UBT, or an improvised condom-UBT [ 78 ]. Although the base case of this analysis estimated the usage of the ESM-UBT to be the dominant strategy, the probabilistic sensitivity analysis (PSA) showed large uncertainty, and the authors could not conclude that switching from improvised devices to ESM-UBT in India would be cost-effective [ 78 ]. The assessment of one further device was identified, the novel Butterfly device for uterine compression [ 80 ]. This device is not yet utilised outside of trials and the results are reported in Table 3 .

Use of blood products for PPH management.

Five studies assessed various strategies for optimising blood product management in women with PPH [ 81 – 85 ]. The first, an economic evaluation from trial data, assessed blood resuscitation for severe PPH guided by point-of-care viscoelastic testing (PCVT) compared to empiric blood product resuscitation in the USA [ 82 ]. The intervention group experienced lower volumes of estimated blood loss, lower hysterectomy and intensive care unit admission rates, and significantly lower hospital costs [ 82 ]. However, the study was low quality, may be at risk of bias related to treatment effect (Table U in S8 Appendix ) and it is unclear if the device-associated costs were included in the analysis.

A high-quality modelling study in the USA attempted to identify the most cost-effective strategy for predelivery blood type, screening, and cross-matching [ 81 ]. Although some strategies were successful at reducing emergency-release transfusions, the upfront costs of predelivery testing outweighed the benefits; the best strategy was no routine admission testing [ 81 ]. Possible bias related to treatment effects could not be assessed (Table U in S8 Appendix ).

One trial-based study in the Netherlands assessed whether women with acute anaemia following PPH should be transfused to a target haemoglobin or treated conservatively with iron and folic acid supplementation [ 85 ]. Although no clear cost-effectiveness threshold was set, the large costs required to lift women’s fatigue and quality of life scores by marginal amounts were not justified from the hospital perspective [ 85 ].

Two modelling studies assessing cell salvage during cesarean section were identified [ 83 , 84 ]. In the UK study, cell salvage in cesarean section compared to no cell salvage incurred $13,714 per donor blood transfusion avoided, and was therefore unlikely to be cost-effective [ 83 ]. In the USA study, a broader study perspective, longer time horizon, and higher effectiveness estimates were used [ 84 ]. The authors concluded that cell salvage when women were at high risk of haemorrhage was likely cost-effective at their stated thresholds [ 84 ]. Both studies were high quality, though possible bias related to treatment effects could not be assessed due to the considerable variability of published effectiveness estimates [ 86 , 87 ].

Treatment algorithms for PPH management.

One study evaluated a PPH treatment algorithm in Switzerland [ 88 ]. Introducing the algorithm resulted in a wider range of PPH treatments being applied in more rapid succession, without showing statistically significant differences in cost or health outcomes [ 88 ].

Referral to higher level care for PPH management

One high-quality modelling study assessed the cost-effectiveness of an emergency interfacility referral and transfer service for women and neonates in rural Madagascar [ 89 ]. The service, which assessed and transported patients from primary level care to secondary level facilities was estimated to be highly cost-effective, incurring $19.82 per additional life year saved for women with PPH. However, these results should be interpreted cautiously as the sub-analysis of women with PPH included only 46 patients, and survival rates were based on expert opinion rather than primary data.

Economic evaluations of PPH bundles

Care bundles are a complex strategy where multiple interventions are used simultaneously [ 90 ]. Three evaluations using effectiveness trial data [ 91 – 93 ], and 1 modelling study [ 94 ] considered care bundles for PPH-related care ( Table 5 ). Two evaluated a combination of preventative and treatment interventions [ 92 , 94 ]. A study in Niger reported a bundle of preventative uterotonics, improvised blood loss measurement and tiered treatment responses was highly effective and incurred low incremental costs [ 92 ]. A USA study showed that PPH preparedness and treatment strategies could be bundled, improving maternal health outcomes and reducing costs [ 94 ].

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Two studies evaluated bundles combining early detection and treatment interventions [ 91 , 93 ]. A study in Wales reported that their bundle—comprising universal risk assessments for PPH, early PPH identification through quantitative measurement, mandatory multidisciplinary team involvement at certain blood loss thresholds, and point-of-care coagulation testing after 1,000 ml blood loss—modestly reduced the proportion of PPH cases progressing to massive PPH, at a cost of $29.16 per patient with PPH > 1,000 ml [ 91 ]. The second study, a health economic evaluation of the E-MOTIVE trial in four sub-Saharan African countries, reported their intervention was highly cost-effective, incurring only $118.10 per DALY averted [ 93 ]. CHEC-E scores and certainty of effectiveness data of the 4 bundle evaluations varied (Table D in S7 Appendix and Table V in S8 Appendix ).

This is, to our knowledge, the first systematic review examining the cost-effectiveness of interventions for PPH across the continuum of prevention, diagnosis, treatment, or combinations of these. We identified 56 studies—approximately half (24 studies) were conducted in high-income settings. Despite this considerable body of economic evidence for PPH-related care, the interventions, evaluation methodologies, time horizons, and perspectives varied considerably between studies. Acknowledging this heterogeneity, some patterns emerged. Currently, no injectable uterotonic agent or combination is universally dominant from a cost-effectiveness perspective. Across 15 studies assessing carbetocin against oxytocin, studies were split as to whether carbetocin improved health outcomes while incurring further costs or saved costs. The single UK study that considered the full range of available uterotonics did not recommend switching away from oxytocin [ 30 , 31 ].

Six studies found that when injectable uterotonics are unavailable using misoprostol is consistently cost-effective over no uterotonic [ 52 – 57 ]. However, the quality of studies was variable, and effectiveness estimates underpinning the cost-effectiveness calculations are inconsistent with recent estimates [ 30 , 37 ]. Studies of tranexamic acid for either prevention or treatment scored high on CHEC-E, used appropriate effectiveness estimates and concluded that the addition of tranexamic acid either dominated or was cost-effective across a range of settings [ 59 – 61 , 72 – 75 ], acknowledging that in some circumstances, the magnitude of the health benefit was small [ 61 ]. The 4 studies assessing the combination of multiple interventions into care bundles—variably involving prevention, diagnosis, and treatment components—suggest this can provide good economic value [ 91 – 94 ], particularly in LMICs [ 92 , 93 ].

Reviewing the effectiveness data used in each study’s cost-effectiveness calculations provided valuable insights. In some economic evaluations, the magnitude of an intervention’s effect was dramatically different to effect estimates reported in reputable systematic reviews. For example, one study’s base-case evaluation was centred around 600 μg of oral misoprostol being more than 6 times more effective at preventing transfer to hospital due to PPH, than 10 IU (international units) of intramuscular oxytocin for women in maternity huts in Senegal [ 47 ]. The trial this estimate was based on only had a single event for this outcome [ 95 ]. In other studies, assessing the cost-effectiveness of misoprostol administered by skilled staff, misoprostol was repeatedly assumed to lower the risk of PPH by 50% to 80% compared to no medication [ 52 , 56 , 57 ]. More recent effect estimates from systematic reviews indicate that it likely reduces the risk of PPH by approximately 25% [ 37 ]. The difference in assumed effectiveness can greatly change the number of expected outcomes, and therefore how cost-effective the intervention is perceived to be. For illustration, in a cohort of 10,000 women giving birth, with a baseline rate of PPH of 6%, altering the assumed effectiveness of misoprostol from reducing risk of PPH by 50% down to 25% would result in an extra 150 cases of PPH, and considerably change the costs used in the evaluation.

Previous systematic reviews have focused only on the cost-effectiveness of uterotonics for prevention [ 11 ], intrauterine devices for treatment [ 12 ], or tranexamic acid for treatment [ 13 ]. Similar to the 2019 review of preventative uterotonics, we were unable to clearly identify a particular agent that performed better from an economic perspective, despite a doubling of included studies. In comparison with the 2020 review on uterine tamponade devices, we identified one further economic evaluation [ 78 ], though economic data on this intervention remains sparse. Since the 2021 review on tranexamic acid for PPH treatment, one further economic evaluation has been published [ 74 ], and its results are compatible with the previous conclusion—that it is likely either cost-saving or cost-effective.

Although there are robust, comparative effectiveness data for the use of injectable uterotonics in PPH prevention [ 37 ], there remains no universally dominant choice from an economic perspective. The most economical choice of uterotonic is context-specific—considering trade-offs in effectiveness, side-effect profile, cost, availability, heat-stability, and the presence of trained providers to administer them. By comparison, the economic rationale for incorporating tranexamic acid into PPH treatment is more straightforward. It is recommended by WHO [ 23 , 29 ] with compelling evidence of benefits [ 96 ], and it has been demonstrated to be cost-saving or cost-effective in diverse settings [ 72 – 75 ]. In contrast, tranexamic acid for PPH prevention is not currently recommended by WHO. Effectiveness evidence of its prophylactic use suggests some benefit in preventing postpartum blood loss [ 7 , 62 , 63 , 97 ], noting that the 3 economic evaluations suggesting that it is a dominant or cost-effective strategy were from high-income settings [ 59 – 61 ]. While the addition of single agents to PPH prevention or treatment protocols can offer clinical and economic benefits, the implementation of combining therapies using a care bundle approach offers another path forward. There is high-quality economic evidence that care bundles can reduce the burden of PPH in LMIC [ 90 , 98 ] at modest incremental costs [ 93 ].

This review identified large gaps in the health economic literature that require further research. Several pivotal PPH interventions—such as oxytocin for treating PPH and quantitative measurement of postpartum blood loss—do not have high-quality economic data. Other interventions, such as PPH prevention using misoprostol have numerous economic evaluations, yet all were based on effectiveness estimates that have been superseded and are therefore of limited utility. Some interventions such as UBT and NASG demonstrated good value economically but have only been evaluated in a small number of studies and settings.

While effectiveness evidence forms the basis for recommendations, cost-effectiveness and resource use data play a key role in their implementability, especially so for resource-limited settings. Thus, effectiveness trials on PPH prevention, diagnosis, and management should have economic evaluations routinely embedded, helping maximise their translation and impact. The E-MOTIVE trial [ 98 ], and its embedded economic evaluation [ 93 , 99 ] is a recent successful example. First-order approximations of how results could translate across settings are possible to an extent with modelling that accounts for different demographics, health system characteristics, baseline intervention coverage and costs. These can be used to inform local, context-specific policies, but should not be used in the absence of considering local acceptability and feasibility. Translatability of results from modelling and our ability to make evidence informed decisions based on their results would also benefit from the creation of more robust methods for evaluating the certainty of economic evaluations [ 100 ].

Strengths of this review include the broad search conducted on multiple databases, with no limitations on language or date, and the systematic methodology employed in screening studies, extracting data, appraising quality, and resolving disputes. In addition, only peer-reviewed, economic analyses including the assessment of both health and financial outcomes were included in this review. Beyond appraising study quality, we also compared the effectiveness data used in each study to up-to-date systematic reviews, to minimise the possibility that economic findings based on outdated effectiveness data had influenced our conclusions.

This review has several limitations. Firstly, it was completed without nominating an ideal setting. Without an ideal setting, no transferability assessment could be completed. It is therefore important that users of the collated and summarised evidence in this review consider the extent to which each study finding is applicable to their own (or a nominated) setting. Secondly, while some major sources of study uncertainty were interrogated through the CHEC-E assessment, the description of differences between study settings and methods, and the in-depth assessment of effectiveness parameters used, other possible sources of uncertainty were not able to be interrogated to the same extent. In particular, a summary of the costing parameters used, and model validation methods undertaken by each study were not completed beyond the requirements of the CHEC-E assessment tool. Thirdly, our review of effectiveness estimates relied on recent systematic reviews; more recent data from single randomised trials, not yet incorporated into meta-analyses, are thus not captured. Fourthly, by choosing to summarise economic evaluations across prevention, diagnosis and treatment of PPH this review has prioritised breadth over the depth of analysis in the main manuscript. More detail, such as an analysis of the most appropriate study perspective and time horizons would have been possible through single intervention reviews on a smaller group of studies. It is important that the results summarised in this review are interpreted in the context of the more detailed information contained in the supplementary materials, namely the study characteristics ( S6 Appendix ), CHEC-E scores ( S7 Appendix ), and the analysis of the effectiveness data used in each study ( S8 Appendix ). Fifthly, several included studies were relatively old—7 were published prior to 2014. While historical cost estimates can be adjusted to present value, the treatment choices, evidence to inform key model parameters, and methodologies used to conduct and report economic evaluations have evolved over time.

This review has collected, summarised, and highlighted important health economic findings from 56 studies across 16 interventions for the prevention, diagnosis, and treatment of PPH. We identified consistent evidence that adding tranexamic acid to PPH treatment regimens is a dominant strategy and that combining PPH interventions into bundles can deliver improved health outcomes for modest cost. We also identified significant gaps in the cost-effectiveness evidence for PPH interventions. Of the 29 WHO recommendations, 16 do not have any cost-effectiveness evidence, and further assessments of widely used interventions for PPH treatment such as additional uterotonics, non-pneumatic anti-shock garment, or uterine balloon tamponade are urgently needed.

Supporting information

S1 appendix. prisma checklist..

https://doi.org/10.1371/journal.pmed.1004461.s001

S2 Appendix. Search strategies.

https://doi.org/10.1371/journal.pmed.1004461.s002

S3 Appendix. Data extraction variables.

https://doi.org/10.1371/journal.pmed.1004461.s003

S4 Appendix. CHEC-Extended questions.

https://doi.org/10.1371/journal.pmed.1004461.s004

S5 Appendix. Excluded studies.

https://doi.org/10.1371/journal.pmed.1004461.s005

S6 Appendix. Characteristics of included studies.

https://doi.org/10.1371/journal.pmed.1004461.s006

S7 Appendix. CHEC-Extended scores.

https://doi.org/10.1371/journal.pmed.1004461.s007

S8 Appendix. Analysis of effectiveness data used in included studies.

https://doi.org/10.1371/journal.pmed.1004461.s008

S9 Appendix. Economic evaluations mapped to WHO recommendations.

https://doi.org/10.1371/journal.pmed.1004461.s009

S10 Appendix. Results presented by region.

https://doi.org/10.1371/journal.pmed.1004461.s010

S11 Appendix. Summary of economic evaluations of oxytocin for prevention.

https://doi.org/10.1371/journal.pmed.1004461.s011

S12 Appendix. Summary of economic evaluations of surgical interventions.

https://doi.org/10.1371/journal.pmed.1004461.s012

Acknowledgments

Lorena Romero MBIT, Research & Training Librarian, The Ian Potter Library, Alfred Health, Melbourne, Victoria, Australia.

Jiaxin Huang, MPH Student, University of Melbourne, Victoria, Australia.

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• Published: 08 September 2024

A systematic review and meta-analysis of HHV-6 and mortality after hematopoietic cell transplant

• Christopher J. Stathis 1 , 2   na1 ,
• Harrison Zhu 2 , 3   na1 ,
• Kristen Carlin 4 ,
• Tuan L. Phan 2 , 5 ,
• Danny Toomey 2 , 6 ,
• Joshua A. Hill   ORCID: orcid.org/0000-0002-7665-7100 7 , 8 , 9   na2 &
• Danielle M. Zerr   ORCID: orcid.org/0000-0003-2944-7554 10   na2  

Bone Marrow Transplantation ( 2024 ) Cite this article

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• Haematological cancer
• Haematological diseases

Human herpesvirus-6B (HHV-6B) reactivation has been associated with non-relapse mortality (NRM) and overall mortality (OM) following allogeneic hematopoietic stem cell transplant (HCT). We performed a systematic review and meta-analysis to better quantify the association. Studies were included if they systematically tested a cohort of HCT recipients for HHV-6 infection or reactivation and described mortality for patients with and without HHV-6B. Random effects models were used to assess the pooled effect of HHV-6B positivity on each outcome of interest. Bayesian aggregation was additionally performed if models included 10 or fewer studies. Eight studies were included in the NRM analysis, which demonstrated a significant association between HHV-6 detection and NRM (pooled effect: 1.84; 95% CI: 1.29–2.62) without significant heterogeneity (I 2  = 0.0%, p  = 0.55). A Bayesian aggregation of the raw data used to construct the NRM random effects model supported these findings (95% credible interval: 0.15–1.13). Twenty-five studies were included in OM analysis, which showed a significant positive association (pooled effect: 1.37; 95% CI: 1.07–1.76), though considerable heterogeneity was observed (I 2  = 36.7%, p  < 0.05). HHV-6 detection is associated with NRM and OM following HCT. Randomized trials are warranted to evaluate if preventing or treating HHV-6B reactivation improves outcomes.

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Introduction.

HHV-6 is a member of the Roseolovirus genus of the beta-herpesvirus subfamily of human herpesviruses [ 1 ]. Human herpesvirus 6 (HHV-6) is the collective name of two HHV-6 species, HHV-6A and HHV-6B. The epidemiology of HHV-6A has not been defined. In contrast, HHV-6B infects most individuals in early childhood and the virus reactivates in 30-70% of HCT recipients [ 2 , 3 , 4 , 5 , 6 ]. Because HHV-6B is the pathogenic species known to reactivate in HCT, the current work focuses on evaluating HHV-6B and mortality [ 7 ]. Risk factors associated with HHV-6B reactivation include receiving allogeneic (versus autologous) HCT, myeloablative conditioning regimen, transplants from unrelated or human leukocyte antigen (HLA)-mismatched donors, and umbilical cord blood transplants [ 3 , 4 , 8 , 9 , 10 , 11 , 12 , 13 ]. HHV-6B reactivation has been associated with subsequent encephalitis, central nervous system (CNS) dysfunction, bone marrow suppression, acute graft-versus-host-disease (aGVHD), cytomegalovirus (CMV) reactivation, lower respiratory tract disease, and mortality [ 2 , 4 , 5 , 8 , 9 , 10 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 ].

While some studies have reported an association between HHV-6B and mortality [ 20 , 22 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ], results have been conflicting [ 37 ]. To date, no prior work has systematically aggregated data from studies of HHV-6B and mortality. The goal of the current study is to fill this gap and characterize mortality outcomes in HCT recipients documented to have HHV-6B reactivation compared to those without HHV-6B reactivation.

A search of the PubMed database was performed using the terms:

(hematopoietic OR stem cell OR cord blood OR bone marrow OR transplant*)

(HHV-6 OR MeSH term: herpesvirus 6 OR HHV6 OR human herpesvirus-6 OR HHV-6B OR HHV6B OR human herpesvirus-6B OR HHV-6A OR HHV6A OR human herpesvirus-6A)

This search was performed according to PRISMA guidelines [ 38 ] on 2/1/24 and returned 1,319 results. Manuscripts (or studies) were screened for the following entry criteria (1) inclusion of a cohort of HCT recipients systematically tested for HHV-6 (2) report of the number of patients with HHV-6 infection or reactivation, and (3) report of the number of patients with at least one outcome of interest. Outcomes of interest included non-relapse mortality (NRM), relapse-related mortality (RM), overall survival (OS), treatment-related mortality (TRM), and overall mortality/all-cause mortality (OM/ACM). In instances where raw data describing an outcome of interest by HHV-6B positivity were unclear or not described, the study’s authors were contacted to request these data.

Definitions

NRM was defined as any mortality not attributable to relapse. ACM and OM were defined as mortality due to any reason. OS was defined as survival during the follow up period. RM was defined as mortality due to relapse of disease. TRM was defined as mortality attributed to any treatment-related cause. Studies that assessed OS or ACM were converted to OM by subtracting the number of patients who survived from the total number of patients whose outcomes were described.

Statistical analysis

Study effect sizes were calculated as odds ratios using the raw data for the number of HHV-6B positive and negative patients who did and did not experience each outcome of interest. Studies that did not include at least 10 patients with and 10 patients without HHV-6B detection were excluded from statistical models. Studies were divided into OM, RM, NRM, and TRM. Random effects models were used to pool the effect sizes using the Mantel-Haenszel method [ 39 ], with a Paule-Mandel estimator for τ 2 [ 40 ] and Hartung-Knapp adjustments [ 41 ]. Models were assessed for heterogeneity using an I 2 test and Cochrane’s Q [ 42 ]. Subgroup analyses by stem cell source (CBT, non-CBT, CBT and non-CBT, or source unclear), age of cohort (adult, pediatric, or both), and follow up period (less than the median follow-up period of all studies, or greater than or equal to the median follow up period of all studies) were performed. These analyses were included in the main results if all subgroups contained at least 3 studies and were otherwise detailed in the supplementary materials (pages 4-6, and 8-10) due to the limited utility of subgroup analyses with a small number of studies.

In models that contained 10 or more studies, publication bias was assessed with a linear regression of funnel plot asymmetry using the algorithm described by Peters et al. [ 43 ] for binary outcome data. In models with 10 or fewer studies, raw data were evaluated with Bayesian aggregation of the treatment effect on the logarithm of the odds ratio (logOR). The rationale for this additional analysis is that Bayesian modeling provides additional context to the results of random effects models that include a small number of studies due to the minimal impact of small datasets on Bayesian inferences. Rubin models with partial pooling and weakly informative priors were used. These models were constructed using the Markov Chain Monte Carlo method using 10 chains set to 20,000 iterations each and were not interpreted if r-hat exceeded 1.05.

Of the 1319 results, 1063 were excluded during screening, leaving 256 articles for full-text review. During full-text review, 185 articles were excluded and 71 articles met inclusion criteria. Among studies that met inclusion criteria, 28 were included in statistical analyses (based on the minimum number of patients required) with a total of 4241 patients included across all studies [ 2 , 20 , 21 , 22 , 30 , 32 , 33 , 34 , 35 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 ]. A PRISMA flowchart detailing reasons for exclusion is provided in Fig.  1 . Characteristics of patients included in analyses are given in Table  1 . A full dataset with all included and excluded studies, along with all collected data and all reasons for exclusion, is provided in Supplementary Table  1 . Mortality data stratified by HHV-6 status is provided in Supplementary Table  2 .

PRISMA Flowchart.

Of the 28 studies included in statistical analyses, 25 provided OM data, 8 provided NRM data, 7 provided RM data, and 1 provided TRM data. Models were not built to assess TRM because only 1 study was identified. Some studies described multiple outcomes of interest and were thus included in multiple analyses. Subgroup analyses for studies assessing OM were included in main results. An insufficient number of studies included the data required for subgroup analyses of RM and NRM; these results are available in the supplementary materials on pages 4-6, and 8-10 for completeness but are not described in the main results.

HHV-6B detection and non-relapse mortality

Eight studies were included in analysis of non-relapse mortality. A random effects model demonstrated a pooled effect size of 1.84 (95% CI: 1.29–2.62, p  < 0.01), indicating that patients with HHV-6B detection had significantly increased odds of NRM (Fig.  2a ). The model did not exhibit significant heterogeneity, with 0% of the observed effects attributed to variation between studies (I 2  = 0.0%, Q = 5.94, p  = 0.55).

a Non relapse mortality associated with HHV-6 positivity: Random effects model. b Non relapse mortality associated with HHV-6 positivity: Bayesian Aggregation.

Due to the small number of studies assessed, a Bayesian aggregation was performed to understand if the observed association may be influenced by the limited number of studies. The hypermean of the aggregate treatment effect on logOR was 0.63, with a 95% credible interval of 0.15 to 1.13 (Fig.  2b ). This model can be interpreted as indicating that there is a 95% probability that patients diagnosed with HHV-6B infection or reactivation were between 15% and 113% more likely to have an outcome of NRM. These results provide reasonable confidence that HHV-6B positivity predicts non-relapse mortality, in support of the random effects model.

HHV-6B detection and overall mortality

Twenty-five studies were included in analysis of overall mortality. A random effects model demonstrated a pooled effect size of 1.37 (95% CI: 1.07–1.76, p  < 0.05), indicating that patients with HHV-6B detection had significantly increased odds of death due to any cause. Significant heterogeneity was observed in the model, with 37% of the pooled effect attributable to between-study heterogeneity (I 2  = 36.7%, Q = 37.9, p  < 0.05). The heterogeneity observed in the model suggests that the observed effect may be due to variation between studies, rather than a true pooled effect. Subgroup analyses did not reveal a significant difference between groups based on stem cell source (Q = 0.55, p  = 0.91; Fig.  3a ), age (Q = 0.90, p  = 0.64; Fig.  3b ), or follow-up period based on a median follow-up period of 100 days (Q = 0.02, p  = 0.88; Fig.  3c ). A test of funnel plot asymmetry did not indicate a significant influence of publication bias on the current results (t = −0.18, p  = 0.85; Fig.  4 ).

a Risk of Overall Mortality with HHV-6 Positivity, Subgroup analysis by Stem Cell Source. b Risk of Overall Mortality with HHV-6 Positivity, Subgroup analysis by Age. c Risk of Overall Mortality with HHV-6 Positivity, Subgroup analysis by Follow-up Period.

Funnel Plot of Studies evaluating Overall Mortality.

HHV-6B detection and relapse mortality

Seven studies were included in analysis of relapse mortality and HHV-6B positivity. A random effects model demonstrated a pooled effect size of 0.74 (95% CI: 0.28–1.96) without significant heterogeneity observed (I 2  = 40.1%, Q = 10.0, p  = 0.12), indicating that HHV-6B detection did not increase the odds of relapse mortality. A Bayesian aggregation was performed due to the low number of studies included, which supported a lack of association (Credible interval: −1.18 to 0.54).

The main objective of the present work was to determine if there was a significant association between HHV-6B reactivation and mortality following HCT. We found that HHV-6B detection is associated with NRM as supported by a significant pooled effect, a lack of heterogeneity, and Bayesian aggregation, while OM is associated with HHV-6B as supported by a pooled effect limited by heterogeneity.

HHV-6B can cause encephalitis [ 63 ] and has been associated with pneumonitis [ 29 ]. However, these complications do not occur frequently enough to explain the degree of increased NRM we observed. A conjecture that more fully explains our findings is that HHV-6B may be involved in immune dysregulation after HCT, which may explain more frequent adverse events such as acute graft-vs-host disease (aGVHD). HHV-6B reactivation has been associated with delayed reconstitution in NK cells [ 64 ], as well as impaired neutrophil [ 65 ] and platelet [ 35 ] engraftment. Most importantly, HHV-6B can efficiently infect CD4 + T cells [ 66 ] and has been shown to decrease T cell reconstitution after HCT [ 67 ]. CD4 + T-cell reconstitution after HCT has been associated with improved outcomes [ 68 , 69 , 70 , 71 ] whereas delayed CD4 + T-cell reconstitution has been associated with increased risk of aGVHD [ 30 ] as well as increased mortality [ 68 , 69 , 70 , 71 ]. Furthermore, some have postulated that HHV-6 may also deplete regulatory CD4 + T cells and increase the likelihood of dysregulated immune responses, like aGVHD [ 66 ]. Studies using mouse models potentially support the theory that HHV-6-mediated immune dysregulation causes aGVHD by demonstrating that pretreatment of allografts with inhibition against OX40, the entry receptor for HHV-6B, results in decreased severity of GVHD [ 72 ]. aGVHD is a significant source of morbidity and mortality after alloHCT [ 73 ] and a 2018 meta-analysis reported that HHV-6 reactivation is independently associated with nearly a 3-fold increased risk of developing grade II to IV acute GVHD [ 23 ]. Further investigation of the role of HHV-6 may play in aGVHD is needed.

Approximately 0.3–2.9% of individuals are known to have HHV-6B or HHV-6A integrated into the chromosome of every nucleated cell, which can be passed down to offspring in a mendelian fashion (iciHHV-6). Consequently, these patients have strikingly and continuously high HHV-6 DNA viral levels in whole blood ( > 5.5 log 10 copies/mL) without necessarily having demonstrated HHV-6 reactivation. It should be noted that antiviral therapy for iciHHV-6 patients in the absence of reactivation is ineffective and would only expose patients to the risk of drug side effects. Thus, it is important to distinguish between active replication and iciHHV-6, which is inconsistently reported in the context of the papers reviewed.

Treatments for HHV-6B disease are limited and there are currently no FDA-approved therapies for HHV-6B disease. Both ganciclovir and foscarnet are used off-label as first line agents for HHV-6 encephalitis [ 74 ]. Unfortunately, use of these antivirals is limited by side effects of myelosuppression (ganciclovir) and nephrotoxicity (foscarnet); for this reason, prophylactic use is not recommended [ 74 ]. Other agents, such as cidofovir have only anecdotal evidence for use [ 7 , 74 ]. Clinical trials exploring the efficacy of viral specific T-cell therapies have been previously attempted but were discontinued due to a low probability of meeting the primary endpoints [ 73 , 75 ]. Artesunate has also recently been studied for its in vitro effect on HHV-6 [ 76 ], but it has not been studied in the context of HSCT. Considering our findings of higher mortality associated with HHV-6B reactivation, there is an urgent need for improved antiviral agents specifically against HHV-6.

Our findings are limited by the following considerations: (1) Despite an available HHV-6 PCR international standard [ 7 , 77 ], this is not widely used to date, and this limits standardization of viral load assessments across studies. (2) Only one database was accessed to perform this systematic review so there may have been literature that was missed including papers with no English translation, poster presentations, abstracts that did not undergo peer review, or other forms of grey literature. (3) Differing treatment methodologies between different hospitals further complicates the analysis due to potential confounding variables not considered such as protocols for the use of foscarnet or ganciclovir for preemptive treatment of HHV-6 or prophylaxis for CMV. (4) The median follow-up period was 100 days, which indicates that many studies have a relatively short follow-up period and highlights the need for studies assessing the effect of HHV-6B on mortality to include longer follow-up periods. Studies with relatively short follow-up periods were included in the interest of gathering comprehensive results. (5) This analysis did not account for viral load, and higher viral loads may be more strongly associated with our outcomes of interest. (6) The analysis did not adjust for confounders that could contribute to HHV-6 detection and/or mortality due to a lack of consistency in covariables across studies. For the purposes of standardization and future meta-analyses, we recommend several covariables be considered when studying outcomes associated with HHV-6B reactivation in this setting, including transplant source, preconditioning regimen, occurrence of GVHD, steroid usage, and CMV reactivation characteristics. Like HHV-6B, CMV is immunomodulatory and independently associated with increased mortality; this could be affecting our analyses, but we are unable to account for the independent contribution of CMV with the available data in the included studies. However, prior work that adjusted for CMV has shown an independent association between HHV-6 and mortality [ 52 ]. 7) Specific contributions to NRM were not consistently available for analysis, so we were unable to provide this data. However, beyond GVHD [ 23 ], there may be other factors contributing to NRM associated with HHV-6B reactivation worth investigating such as encephalitis, hepatitis, pneumonitis, myelosuppression, neutropenic fever, nephrotoxicity, and rash. 8) Publication bias was evaluated using a regression of funnel plot asymmetry, and it is possible that this method does not account for all sources of publication bias.

In conclusion, we demonstrate that HHV-6B reactivation was associated with increased NRM and weakly associated with OM in a meta-analysis of 28 studies. Due to the biological consequences of HHV-6B, HHV-6B activity might contribute to a higher NRM. These results provide quantitative context for prior work establishing a link between HHV-6B and NRM and suggest the possible need for improved therapeutic strategies to manage HHV-6B reactivation after HCT. It is critical to note that the current results suggest a correlative, but not causative, relationship between HHV-6B and mortality. Future studies must carefully account for variables that could contribute to mortality, such as the reactivation of other herpesviruses.

Data availability

All scripts used to perform analyses and generate figures and all raw data used in analyses are publicly available at https://github.com/dannytoomey/hhv6-mortality-ma .

Code availability

Analyses were performed using the R programming language, version 4.3.2. All scripts and raw data used in analysis are publicly available on GitHub [ 78 ].

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Acknowledgements

The authors would like to thank the HHV-6 Foundation for their support of this work.

Author information

These authors contributed equally: Christopher J. Stathis, Harrison Zhu.

These authors jointly supervised this work: Joshua A. Hill, Danielle M. Zerr.

Authors and Affiliations

Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

Christopher J. Stathis

HHV-6 Foundation, Santa Barbara, CA, 93108, USA

Christopher J. Stathis, Harrison Zhu, Tuan L. Phan & Danny Toomey

Baylor College of Medicine, Houston, TX, USA

Harrison Zhu

Seattle Children’s Research Institute, Seattle, WA, USA

Kristen Carlin

Division of Hematology, Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA

Tuan L. Phan

Geisinger Commonwealth School of Medicine, Scranton, PA, 18509, USA

Danny Toomey

Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA

Joshua A. Hill

Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA, USA

Department of Medicine, University of Washington, Seattle, WA, USA

Seattle Children’s Research Institute and Department of Pediatrics, University of Washington, Seattle, WA, USA

Danielle M. Zerr

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CS and HZ designed the study, performed data collection, wrote the manuscript, and prepared submission materials. KC designed and reviewed statistical analyses. TP and DT reviewed the data, performed data analysis, and assisted with manuscript revisions. JAH and DMZ provided expert review of all materials and assisted in project design.

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CS, HZ, KC, TP, and DT have no conflicts to disclose. JAH provides consulting for Allovir, Gilead, Karius, Symbio, and receives research support from Allovir, Gilead, Karius, and Merck. DMZ received research funding from Merck and served as a consultant for AlloVir by serving on clinical endpoint adjudication committees for two studies.

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Sup table 1 - full dataset - mortality after hct and hhv-6.xlsx, sup table 2 - mortality by hhv-6 status.xlsx, supplementary materials, rights and permissions.

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Stathis, C.J., Zhu, H., Carlin, K. et al. A systematic review and meta-analysis of HHV-6 and mortality after hematopoietic cell transplant. Bone Marrow Transplant (2024). https://doi.org/10.1038/s41409-024-02398-w

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Received : 15 April 2024

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Published : 08 September 2024

DOI : https://doi.org/10.1038/s41409-024-02398-w

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• Volume 14, Issue 9
• Comparative effects of sacubitril/valsartan and ACEI/ARB on endothelial function and arterial stiffness in patients with heart failure: a protocol for systematic review and meta-analysis
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• Zhiyong Ma 1 ,
• Zhijie Fu 2 ,
• Shanying Huang 1 ,
• http://orcid.org/0000-0002-1727-0125 Lingyi Chi 3
• 1 Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Department of Cardiology, Qilu Hospital, Cheeloo College of Medicine, Shandong University , Jinan , Shandong , China
• 2 Department of Otorhinolaryngology , The First Affiliated Hospital of Shandong First Medical University , Jinan , Shandong , China
• 3 Department of Neurosurgery , Shandong University , Jinan , Shandong , China
• Correspondence to Dr Lingyi Chi; 13573148930{at}139.com

Introduction Heart failure (HF) is a complex syndrome that affects millions of people worldwide and leads to significant morbidity and mortality. Sacubitril/valsartan, a combination drug consisting of a neprilysin inhibitor and an angiotensin receptor blocker (ARB), has shown a greater improvement in the prognosis of HF than ACE inhibitors (ACEI) or ARB. Recent studies have found that ACEI/ARB or sacubitril/valsartan can increase flow-mediated dilation (FMD) and reduce pulse wave velocity (PWV), which are independent predictors of cardiovascular events and HF prognosis. The purpose of this study is to assess and compare the effect of sacubitril/valsartan and ACEI/ARB on FMD and PWV using meta-analysis and further provide a reference for the role of sacubitril/valsartan in the treatment of HF.

Methods and analysis Clinical randomised controlled trials investigating the effect of sacubitril/valsartan and/or ACEI/ARB on FMD and PWV in patients with HF will be searched in the relevant database, including PubMed, Web of Science, Embase, Cochrane Library and China’s National Knowledge Infrastructure up to January 2024. The outcomes of interest are changes in endothelial function assessed by FMD and changes in arterial stiffness assessed by PWV. The risk of bias was evaluated using the revised Cochrane risk of bias tool for randomised trials (RoB2.0). Review Manager V.5.3 software is used for meta-analysis data synthesis, sensitivity analysis, meta-regression analysis, subgroup analysis and risk of bias assessment. The reporting bias of studies will be evaluated using the funnel plot, in which symmetry will be assessed by Begg’s and Egger’s tests. The evidence quality of the included studies will be evaluated by the Grading of Recommendations Assessment, Development, and Evaluation.

Ethics and dissemination This study only analyses research data from the published literature and therefore does not require ethical approval. We will submit the systematic review to a peer-reviewed journal.

PROSPERO registration number CRD42024538148.

• Heart failure
• Meta-Analysis
• Protocols & guidelines

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjopen-2024-088744

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Strengths and limitations of this study

This systematic review and meta-analysis will assess the effect of sacubitril/valsartan on endothelial function and arterial stiffness in heart failure.

Eligible studies will be selected using strict inclusion and exclusion criteria.

The risk of bias and the evidence quality will be evaluated by the Cochrane guidelines and the Grading of Recommendations Assessment, Development, and Evaluation methodology.

The clinical heterogeneity due to different treatment frequency and language bias due to the inclusion of both English and Chinese literature may be the limitations.

Introduction

Heart failure (HF) is a complex syndrome that affects millions of people worldwide and often leads to significant morbidity and mortality. 1–3 There are more than 64 million patients worldwide with a 1–3% incidence of HF in Europe/America and a 1.3% incidence in China, which has become a serious public health issue. 1 3 4 The pathophysiology of HF involves multiple mechanisms, of which vascular dysfunction plays an important role in regulating the preload and afterload of the heart and coronary circulation. 5–8 Increasing data revealed that endothelial function and arterial stiffness are important markers of vascular function and independent predictors of the prognosis of HF. 8 9 Flow-mediated dilation (FMD) and pulse wave velocity (PWV) have been widely used to assess endothelial function and arterial stiffness. In clinical studies, every 1% increase in FMD is associated with an 8–13% lower risk of fatal and nonfatal cardiovascular (CV) events and/or deaths from all causes. 10 11 Similarly, a 1 m/s increase in PWV has been associated with a 15% increase in CV mortality and all-cause mortality. 12 13 Therefore, therapeutic strategies targeting endothelial function and arterial stiffness are crucial to improve outcomes in patients with HF.

Among the various pharmacological agents used in HF, ACE inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs) have long been the mainstay of treatment. 1–3 14 These drugs work primarily by blocking the renin–angiotensin–aldosterone system, a key hormonal pathway involved in the pathophysiology of HF. 15 In recent years, sacubitril/valsartan, a combination drug consisting of a neprilysin inhibitor and an ARB, has become one of the first-line drugs for the treatment of HF. 16 The core clinical trial, Prospective Comparison of ARNI with ACEI to Determine Impact on Global Mortality and Morbidity in Heart Failure, revealed that sacubitril/valsartan reduced all-cause mortality by 16% and CV disease mortality by 20% and decreased the rate of hospitalisations related to HF by 21% compared with standard ACEI enalapril therapy in patients with HF with reduced ejection fraction (EF). 17 Even in patients with pre-HF with preserved EF, the Patients With Natriuretic Peptide Elevation trial showed that sacubitril/valsartan versus valsartan resulted in a greater increase in the left atrial volume index and a decrease in the N-terminal pro-brain natriuretic peptide (BNP). 18 Furthermore, sacubitril/valsartan significantly reduces BNP levels and improves quality of life and ventricular remodelling in patients with HF more than ACEI/ARB. 19 Therefore, sacubitril/valsartan has significant protective effects on the CV system compared with traditional ACEI/ARB medications.

Previous studies have found that ACEI/ARB or sacubitril/valsartan can increase FMD and reduce PWV. 20–22 Sacubitril/valsartan improved endothelial dysfunction and arterial stiffness in patients with chronic HF probably related to reduced oxidative stress, platelet activation and circulating inflammation biomarkers, without adverse effects. 23 24 Surprisingly, there is no comprehensive review on the different effects of sacubitril/valsartan and ACEI/ARB on endothelial function and arterial stiffness of HF patients. Therefore, we conducted an exhaustive systematic review and meta-analysis to explore whether sacubitril/valsartan can provide further improvements in endothelial function and arterial stiffness compared with traditional ACEI and ARB agents.

The purpose of this systematic review and meta-analysis is to evaluate the comparative effectiveness in endothelial function and arterial stiffness between sacubitril/valsartan and ACEI/ARB in the management of HF from clinical randomised controlled trials (RCTs).

Methods and analysis

Patient and public involvement.

Patient and public are not involved in the design or conduct of the study.

Eligibility criteria

Types of studies.

RCTs investigating the effect of sacubitril/valsartan, ACEI and/or ARB on endothelial function/FMD and arterial stiffness/PWV in patients with HF will be included. Cross-sectional studies, non-RCTs, case series, case reports, reviews, commentaries and animal studies will be excluded.

Types of participants

The patients were diagnosed with acute or chronic HF according to the ‘ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure’ or the ‘ACCF/AHA guideline for the treatment of heart failure’ or the ‘Guidelines for the Diagnosis and Treatment of Heart Failure in China’. 1–3 Patients with acute coronary syndrome, cancer, pregnancy, rheumatic disease and systemic infection diseases were excluded.

Type of interventions and comparisons

Conventional treatment for HF plus sacubitril/valsartan versus conventional treatment for HF including ACEI and/or ARB was included. Conventional treatment for HF includes diuretic, β-blocker, mineralocorticoid receptor antagonist and/or cardiotonic and/or vasodilator.

The outcomes of interest are changes in endothelial function assessed by FMD (%) and changes in arterial stiffness assessed by PWV (m/s). The basic effects of sacubitril/valsartan on all-cause and CV disease mortality, the rate of HF-related rehospitalisations and the EF are also analysed.

Methods of obtaining and analysing data

Literature search and study selection.

Two authors carried out independent searches of databases including PubMed, Web of Science, Embase, Cochrane Library and China National Knowledge Internet (CNKI) database up to January 2024. The search strategy combined medical subject headings and free text terms such as the following: ‘HF’ OR ‘chronic heart failure (CHF)’ AND ‘sacubitril / valsartan’ OR ‘angiotensin converting enzyme inhibitor (ACEI, including enalapril, ramipril, captopril, lisinopril or trandolapril)’ OR ‘angiotensin receptor blocker (ARB, including valsartan, candesartan or losartan)’ AND ‘endothelial function’ OR ‘flow-mediated dilation (FMD)’ OR ‘arterial stiffness, OR ‘pulse wave velocity (PWV)’. In addition, other resources from Google Scholar, Baidu Scholar, Clinical Trials.Gov and Chinese Clinical Trial Registry were also searched to avoid grey/unpublished trials. We also manually searched the reference lists of the enrolled studies to find studies relevant to the study topic. The search strategy is shown in online supplemental additional file 1 . Only RCTs in English or Chinese were included in the analysis, and there was no restriction on the publication year. The literature selection based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 25 is shown in figure 1 .

Supplemental material

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PRISMA flow chart for the study selection process. CNKI, China National Knowledge Infrastructure; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

Assessment of risk of bias and data extraction

The risk of bias was evaluated by two authors using the revised Cochrane risk of bias tool for randomised trials (RoB2.0) . 26 The potential types of bias included the following: randomisation bias, deviation bias for the intended intervention, bias from missing data, bias from outcome measurements and bias due to the selection of reported data. The Review Manager (RevMan) V.5.3 was used to generate bias graphs and summary of risk of bias. Reporting bias of the studies will be evaluated by the funnel plot, in which the symmetry will be evaluated using Begg’s and Egger’s tests. 27

A standard form was used for data extraction that included information on study characteristics (title, first author, publication year and study design), demographic data of participants (inclusion criteria, sample size, sex, age and baseline status), treatment details (name of the drug, dose and duration of treatment) and results related to endothelial function and arterial stiffness. We excluded studies without sufficient information. Disagreements were resolved by consensus.

Data analysis

RevMan V.5.3 software developed by the Cochrane Collaboration was used to compare the effects of different treatment strategies on endothelial function and arterial stiffness. All outcomes will be continuous variables and were expressed as weighted mean differences with 95% CI. Statistical heterogeneity between selected articles was tested using χ 2 test and I 2 test. An I 2 value of >50% indicates statistically significant heterogeneity in the selected studies. 28 All analyses were initially done using a fixed-effects model, and if heterogeneity between studies was observed, the analysis was repeated using a random-effects model, which includes a measure of variance in the calculation of the pooled results. To establish the effect of clinical heterogeneity of the included studies on the results of the meta-analysis, a subgroup analysis was performed. P  < 0.05 was considered statistically significant.

Quality of evidence

The evidence quality of the included studies will be evaluated by the Grading of Recommendations Assessment, Development, and Evaluation. 29 The limitations of the study, inconsistencies of method and results, indirect evidence, inaccuracy and publication bias will be assessed. Evidence will be categorised into four levels: high, moderate, low or very low.

Ethics and dissemination

This study only analyses research data from the published literature and therefore does not require ethical approval. We will submit the systematic review to a peer-reviewed journal.

Ethics statements

Patient consent for publication.

Not applicable.

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Contributors ZM, ZF and NL drafted the article. All authors contributed to the development of the selection criteria, the risk of bias assessment and data extraction. ZM, ZF and SH developed the search strategy. ZF, NL and SH provided statistical expertise. All authors approved the final version of the manuscript. LC is the guarantor of this work.

Funding This work was supported by the Shandong Province Science and Technology Research Program (No. ZR2020MH038) and the National Natural Science Foundation of China (Nos. 81700891 and 81470558).

Disclaimer The sponsor has not taken part in study design, data collection and analysis, decision to publish or manuscript preparation.

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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A systematic literature review on determinants and outcomes of ESG performance in family firms

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• Published: 09 September 2024

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• Ramona Waldau   ORCID: orcid.org/0009-0007-4410-2892 1  

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As the predominant business type, family firms hold a unique position to influence the global sector’s ESG footprint. However, research on their ESG activities and performance is complex, multi-layered, and currently lacks integration. This review aims to bridge these research disciplines by providing an integrative overview of the current state of family firm ESG literature. By systematically reviewing 127 peer-reviewed studies published between 2000 and mid-2024, I examine the determinants and outcomes of family firm ESG performance, synthesize existing knowledge, and suggest future research directions. The findings reveal the nuanced and at times ambiguous role of family involvement across different ESG dimensions. Additionally, methodological challenges have contributed to inconclusive results in certain areas. This literature review identifies several promising new directions for future research at the intersection of family firm and ESG research to enhance our understanding and foster a more integrated and comprehensive approach to studying ESG in family firms.

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1 Introduction

The influence of family involvement in relation to environmental, social, and governance (ESG) topics has been the focus of numerous recent studies. Family firms (FFs) have a great impact on the ecological and social footprint of the global private business sector due to their ubiquity and economic contribution (La Porta et al. 1999 ; De Massis et al. 2018 ). Therefore, it is crucial for researchers, practitioners, and policymakers to ask the following question: “What factors determine FFs’ ESG activities and performance, and what are the outcomes of FFs’ ESG activities and performance?” However, the relationship between FFs and their ESG activities and performance is proven to be complex and multi-layered. Some researchers find that certain FF subsystems, particularly ownership, positively impact specific aspects of ESG activities and performance, while others report negative effects (e.g., Rees and Rodionova 2015 ; Bammens and Hünermund 2020 ). A key concept explaining the effect of family ownership on ESG activities and performance is socioemotional wealth (SEW), which is considered to be the most important characteristic distinguishing FFs from all other organizational forms (Berrone et al. 2012 ). SEW is defined as the non-financial aspects that fulfill the emotional needs of the owning family (Gómez-Mejía et al. 2007 ), such as identification of family members with the firm or renewal of family bonds through firm succession (Berrone et al. 2012 ). Given the complexity of both FF subsystems and ESG issues, along with the increasing number of studies that bridge these areas from various research fields—including FF, corporate social responsibility (CSR), sustainability, and management—an integrative review of the current state of research and a future research agenda are necessary and timely.

Few literature reviews recognize the importance of linking FF and ESG research and highlight the role of FFs in the context of individual ESG issues (e.g., Feliu and Botero 2016 ; Ferreira et al. 2021 ; Mariani et al. 2021 ). This literature review differs from previous ones that focused only on parts of the ESG concept. Instead, I paint a broader picture by including studies analyzing both ESG dimensions and FF subsystems and by suggesting future research directions based on both streams. Thereby, determinants of ESG activities and performance in FFs refer to the factors influencing whether, how frequently, or how effectively FFs engage in ESG topics, as defined below. Outcomes of ESG activities and performance stand for the non-financial or financial results and other effects of FFs’ actions regarding ESG topics. The purpose of this literature review is to collect, structure, and synthesize existing knowledge on the determinants and outcomes of ESG activities and performance in FFs, and to propose avenues for future research. A deeper understanding of these relationships is crucial, especially as ESG considerations gain importance (Kiesel and Lücke 2019 ) and FFs play a significant role in global economies (De Massis et al. 2018 ). This review aims to uncover trends, highlight research gaps, and address inconsistencies to guide future studies towards areas needing further exploration. The synthesis enhances our understanding of how ESG activities and performance of FFs are uniquely shaped, ensuring that future research is both comprehensive and focused on these critical yet under-researched aspects of significant economic relevance.

This article employs a systematic review process (Webster and Watson 2002 ) to synthesize the findings of 127 peer-reviewed studies published between 2000 and mid-2024. These studies represent the current body of knowledge from the intersection of ESG and FF with high levels of relevance and scientific rigor, as only publications from journals ranked 3 and above in the Academic Journal Guide by the Chartered Association of Business Schools (CABS 2021 ) are included in this review. The latter differentiates the foci of the reviewed studies in terms of FF subsystems (Pieper and Klein 2007 ) and ESG dimensions (Li et al. 2021 ). The findings indicate that researchers have primarily focused on identifying determinants of ESG performance differences between FFs and non-FFs by measuring the level of family ownership. However, less attention has been paid to the heterogeneity among FFs, the actual measurement of FF goals, and ESG performance outcomes. These gaps present numerous opportunities for future research.

The study contributes to extant research in two ways. First, by addressing the fragmented body of studies, this review synthesizes the current state of knowledge, creating a consolidated framework that integrates diverse findings and perspectives. This comprehensive approach helps identify areas where data may be conflicting or incomplete, guiding future investigations. The added value of this synthesis lies in its ability to provide a coherent narrative and actionable insights, which are crucial for advancing the field and informing both theory and practice. Second, this review aims to bridge the gap between FF and ESG research, specifically targeting scholars in both fields. My goal is to encourage these researchers to transfer knowledge between both streams, considering the unique aspects of ESG performance in FFs and its implications for other types of organizations. This is particularly relevant for ESG scholars interested in non-economic behaviors and FF scholars focused on ESG issues. By fostering interdisciplinary collaboration, this review seeks to enhance the understanding and application of ESG principles in FFs.

2 ESG dimensions across FF subsystems

ESG dimensions. Environmental, social, and governance dimensions, nowadays known by their acronym ESG, were introduced as significant extensions to investment criteria in global financial markets (Christensen et al. 2022 ) and have since evolved into a central framework through which firms integrate ESG concerns into their operations and activities (Gillan et al. 2021 ). Increasing interest from investors, customers, and policymakers, as well as ESG’s ubiquity and comprehensiveness, has led to a growing number of researchers investigating the determinants and outcomes of ESG performance in various contexts (e.g., Friede et al. 2015 ; Widyawati 2020 ; Gillan et al. 2021 ). By employing the ESG concept in this review, the broadest definition of corporate responsibility is applied to ensure a holistic overview (Hubbard 2009 ; Capelle-Blancard and Petit 2017 ). I draw on the ESG framework by Li et al. ( 2021 ), which is based on the glossary and definitions by the European Banking Authority. As ESG categories continuously evolve and clarify, their taxonomy provides a well-founded framework for the definition of each ESG dimension. Similar definitions of each dimension have also been used by other researchers, such as Berg et al. ( 2022 ). Environmental activities and performance refer to a firm’s impact on the natural environment, including biodiversity, energy, water, waste management, and greenhouse gas emissions. Social activities and performance are linked to a firm’s impact on stakeholders, such as product quality and safety, community relations, and employee health and safety. Governance activities and performance involve evaluating a firm’s strengths and concerns regarding aspects like business ethics, board diversity, corruption, taxes, reporting, and remuneration.

In this literature review, I examine ESG activities and performance as quantitatively measured and evaluated by researchers, using predefined variables to compare firms. Common metrics include the KLD ratings, which have been employed to aggregate strengths and weaknesses in each ESG aspect to calculate an overall ESG performance score (e.g., Wagner 2010 ; Cui et al. 2018 ; Lamb and Butler 2018 ). However, the lack of standardized metrics and methodologies across rating agencies poses challenges for consistent assessment and comparability between firms (Berg et al. 2022 ). Thus, I propose that future research explore additional ESG measures beyond ESG and CSR ratings, as discussed in the discussion.

FF subsystems. FFs inhibit characteristics that distinguish them from other forms of organization, such as their SEW (Berrone et al. 2012 ). As a result, FF research has become a distinct and rapidly growing field within management research (e.g., Gedajlovic et al. 2012 ). FFs are defined by the family’s control through ownership and/or management, guiding the company’s vision and strategy across generations (Chua et al. 1999 ). To address the growing breadth of topics investigated in FF research (Zahra and Sharma 2004 ), I build on the “bulleye” framework by Pieper and Klein ( 2007 ). This model accounts for the idiosyncrasies and heterogeneity of FFs by differentiating between six subsystems: individual, family, ownership, management, business, and environment, which represent the multiple level of analysis relevant for FFs. A firm qualifies as an FF when the family and business subsystems interact with each other (constituting subsystems), while the ownership and management subsystems establish the connection between the FF as a business entity and the family itself (connecting subsystems). This framework has also been used to structure and synthesize findings in other literature reviews on FF research (e.g., Labaki et al. 2019 ; Williams et al. 2019 ).

All following definitions and examples are based on Pieper and Klein ( 2007 ). First, the individual subsystem is the basic level of analysis, representing the human element of FFs. Relevant dimensions include characteristics, intentions, and beliefs of individual family or non-family managers and members related to the FF (Pieper and Klein 2007 ). Second, the family subsystem refers to the nuclear and extended group of related persons (Rothausen 1999 ; Pieper and Klein 2007 ). Exemplary dimensions are involved generations and state of lifecycle, values and goals of the family, and feelings towards each other and the FF, such as love, trust, or commitment. Third, the ownership subsystem stands for the level of firm ownership in form of voting rights or company capital. Relevant dimensions for this subsystem are, for instance, the number of owners, the percent of equity held by a family, and the stage of ownership (Pieper and Klein 2007 ). Fourth, the management subsystem comprises the board and top management team, which may include varying shares of family and non-family managers. Relevant dimensions include the composition of the board or management team, leadership style, and characteristics (Pieper and Klein 2007 ). Fifth, the business subsystem refers to the FF as an organization with inputs and outputs (Thompson 1967 ; Katz and Kahn 2015 ), including financial and non-financial returns, market position, strategic approaches, resources, and capabilities (Pieper and Klein 2007 ). Finally, the environment subsystem encompasses the other subsystems, as FFs operate in distinctive surroundings with different cultural, economic, and physical characteristics, which influence their attitudes and behaviors. Relevant dimensions are FFs’ location and country, cultural system, and stakeholders such as customers, government, or competitors (Kast and Rosenzweig 1992 ; Pieper and Klein 2007 ).

These dimensions highlight the complexity and scope of current FF ESG research and serve as structural criteria for all studies reviewed. To the best of my knowledge, no other literature review has analyzed the determinants and outcomes of ESG performance in FFs. Instead, researchers have focused on narrower research fields, such as CSR (Mariani et al. 2021 ), sustainability (Ferreira et al. 2021 ) or philanthropy (Feliu and Botero 2016 ). This literature review makes an important contribution by structuring and synthesizing the complex and heterogeneous multitude of studies from various research fields dealing with the ESG activities and performance of FFs.

3 Methodology

3.1 search and analysis process.

FF researchers have identified numerous determinants and outcomes of various dimensions of ESG-related topics. As shown in Fig.  1 , a systematic search, review, and analysis process is applied to ensure transparency and comprehensiveness (Webster and Watson 2002 ).

Overview on search and analysis process

Step 1: Search and selection. First, I followed a four-stage search and selection process to ensure that all relevant literature is included:

Broad search . The first step comprised the broad search in popular and comprehensive databases, namely Ebsco Business Source Premier , Elsevier ScienceDirect , Web of Science, and ABI Inform (e.g., Calabrò et al. 2019 ). Based on the definitions in the previous chapter, various keywords were used to search titles and abstracts to gain a comprehensive overview of the research topic: (“esg” OR “csr” OR “sustainab*” OR “corporate social resp*”) AND (“family control*” OR “family firm*” OR “family business*" OR “family ownership*” OR “family-owned*”). To ensure adequate levels of scientific quality and novelty of studies, articles were required to be from peer-reviewed journals ranked 3 and above in the Academic Journal Quality Guide (Paul and Criado 2020 ; CABS 2021 ; Davidsson and Gruenhagen 2021 ), written in English, and published from the year 2000 onwards. These are common inclusion criteria in recently published literature reviews (e.g., Waldkirch 2020 ; Debellis et al. 2021 ). My search yielded 1,323 articles, of which 898 articles remained after removing duplicates from merging results from different databases. Finally, 214 unique articles were admitted to the next step after eliminating all studies from journals either unranked or ranked 2 and below (CABS 2021 ).

Title and abstract analysis. The second step aimed to exclude non-relevant publications detected in the broad search. Initially, I reviewed the titles and abstracts of all articles, eliminating those that did not include FFs and any of the above-described ESG dimensions, as keywords are used with varying meanings. For example, Ahmad et al. ( 2021 ) use the term “sustainability” as a synonym to longevity, referring to a FF’s ability to endure beyond the founder's career, rather than in the context of ESG-related sustainability. This step resulted in a reduced sample of 104 studies.

Full text assessment. I retrieved and read the full texts of all relevant articles to assess their relevance for this review, as titles and abstracts leave open questions to the articles’ purpose, methodology, and findings. The inclusion criteria required that a publication include both perspectives on FFs and any ESG-related topic, but not be a literature review. For instance, studies covering SME without also analyzing (family) ownership structures were excluded (e.g., Russo and Perrini 2010 ). This step yielded 79 relevant studies.

Hand searching. The third step ensured comprehensiveness of my findings. I cross-checked the articles cited in already found articles to yet unknown studies. Additionally, I scanned other related literature reviews (Feliu and Botero 2016 ; Ferreira et al. 2021 ; Mariani et al. 2021 ) to ensure no relevant research was missing. I identified additional 48 relevant studies, a share comparable to other systematic literature reviews (Calabrò et al. 2019 ). Thus, 127 papers were selected for the analysis process.

Step 2: Coding and analysis. Second, I followed a clear coding scheme and analysis process:

Coding. First, I openly coded all publications to identify patterns of repeated topics within this research stream. Subsequently, I searched for an established framework in FF literature that matched my coding insights. Finally, I developed the coding scheme presented in Tables 1 and 2 after refining my main and sub-categories (Wolfswinkel et al. 2013 ). This final coding scheme was applied for all articles, considering their respective methodology, sample, theoretical perspective, FF subsystems, dependent and independent variable(s) analyzed including key FF variable(s), ESG dimensions, definition of ESG variable(s), and overarching findings. Unless otherwise indicated by the authors, I assumed that firm samples included both private and listed firms. This coding result served as the basis for structuring and analyzing all papers in the following steps as well as the descriptive results in the next subchapter. Tables 1 and 2 show a summarized version of this coding result, organizing studies by FF subsystem, ESG dimensions, type (comparative vs. heterogeneity studies), and alphabetically.

Structuring. Based on this coding, I organized all studies in a matrix structure (Webster and Watson 2002 ) as shown in Table  1 , providing an overview on the focus areas of all reviewed studies. This 6 × 4-matrix is based on the six FF subsystems and the four ESG dimensions as described in chapter 2. If publications included variables from multiple FF subsystems, such as ownership and management variables in the study by Cuadrado-Ballesteros et al. ( 2015 ), the FF subsystem that best aligned with the authors’ research question and analytical focus was selected. Table 1 also specifies whether the sample represents a comparative study (differences between non-FFs and FFs) or a heterogeneity study (differences among FFs), helping to clarify the studies’ purpose and methodology.

Analysis. I analyzed the main findings of all publications within each matrix field and across matrix fields to understand the current state of research findings. Subsequently, I synthesized these insights in the following chapter and deducted potential avenues for future research in the final chapter. Since it is not feasible to discuss all articles in detail, I concentrated the summary and synthesis on findings that link FF variables as determinants or outcomes to ESG actions and performance, excluding results that pertain to other relationships.

3.2 Descriptive results

This review analyzes 127 articles, 68 of which were published since 2020, highlighting the rapid expansion and growing importance of ESG-related research. This surge in recent publications aligns with insights from previous literature reviews on FF research (Waldkirch 2020 ; Fries et al. 2021 ). Given the fast-paced developments in this field, a comprehensive literature review that integrates the most recent findings is more necessary than ever.

A few outlets account for a substantial share of the published studies with the Journal of Business Ethics taking the lead (31 articles; 24%), followed by Business Strategy and the Environment (20 articles; 16%) and Family Business Review (11 articles; 9%), indicating that FF ESG research is mainly published in specialized journals for ethics, sustainability, or FF research.

The theoretical development of the studies’ hypotheses is based on a limited set of theories, with the most frequently used perspective being SEW (37 articles; 30%), followed by atheoretical articles (28 articles; 23%), and agency theory (24 articles; 20%). The study by Berrone et al. ( 2010 ) potentially contributed to this trend, linking FFs’ desire to protect their SEW to superior environmental performance and being one of the most cited article in this review with more than 2,200 citations as of July 2024. However, the relatively large share of atheoretical articles suggests a potential lack of integrating theories and constructs from the FF domain into ESG research.

Most studies follow a quantitative approach (117 articles; 92%), with 79 articles using secondary data (62%). This approach is common due to the availability of ESG performance indicators. For instance, ESG ratings or databases, such as the MSCI ESG database, are frequently used to estimate firms’ ESG performance (e.g., Wagner 2010 ; Lamb and Butler 2018 ), while firms’ homepages and sustainability reports offer insights into ESG disclosure (e.g., Arena and Michelon 2018 ). Only 7 studies (6%) derived their insights from a qualitative approach and three were conceptual (2%). This dominance of quantitative research indicates a current focus on measurable activities rather than analyzing underlying motivations related to FFs’ ESG initiatives.

Given the specific nature of this line of research, it is also worthwhile to better understand the samples of the studies. The use of secondary data allows for analyzing time series data and large sample sizes. For instance, Dal Maso et al. ( 2020 ) were able to analyze 33,901 firm-years of 4,932 individual firms from 2002 to 2016 across 56 countries by leveraging external data sources. Geographically, most studies analyzed US-American businesses (36 articles; 28%), followed by studies with a multi-country approach (17 articles; 13%) and Chinese firms (16 articles; 13%). The large number of studies comparing FFs and non-FFs (88 articles; 69%) highlight the great interest in understanding how ownership structures relate to ESG activities. Researchers have focused more on investigating the determinants of ESG performance (106 articles; 83%) rather than the outcomes (21 articles; 17%).

The analysis of the literature reveals an imbalance in favor of studies comparing FFs with non-FF rather than exploring FF heterogeneity. Research has primarily focused on the ownership and business subsystems, as well as overarching ESG and environmental performance, with a greater emphasis on identifying determinants rather than outcomes. Figure  2 visualizes the findings from all studies reviewed, indicating the frequency (n) of studies analyzing each combination of FF subsystem and ESG dimension. Additionally, the main FF topics investigated within each cell are noted. Harvey balls indicate the level of conclusiveness of research findings within that FF subsystem—the fuller the Harvey ball, the more conclusive the results have been. Based on the detailed synthesis below, potential areas for future research are highlighted and will be discussed in the following chapter.

Framework for the current state and future research avenues in FF ESG research

4.1 Individual subsystem

Ten studies have examined the influence of individual managers or CEOs on FF’s ESG activities and performance, highlighting how individual attitudes, religious beliefs, and character traits shape these activities. However, this area of research is still in its infancy compared to CEO research outside the ESG context (e.g., Kaplan et al. 2012 ). Research on the individual subsystem stands out for two reasons. First, it more frequently examines heterogeneity among FFs (n = 7) than comparing FFs to non-FFs (n = 3), acknowledging that family control is highly personalized and dependent on individual willingness (Fassin et al. 2011 ). Second, nearly all studies use a broad range of theoretical perspectives, such as SEW (Bhatnagar et al. 2020 ) or upper echelons theory (Luo et al. 2024 ), suggesting a higher integration between FF and ESG research. This may explain the consistent results in this subsystem and inspire other researchers to base their studies on theoretical foundations applicable to other subsystems.

Five studies focused on the effect of religious beliefs or individual values on FFs’ ESG activities, often using qualitative research approaches due to the strong human nature of this topic. These studies argue that religious beliefs and community-oriented values drive ESG activities for non-financial reasons, promoting a sense of responsibility and selflessness in favor of the needs of FFs’ environment and stakeholder (Fassin et al. 2011 ; Bhatnagar et al. 2020 ; Vu et al. 2024 ). Quantitative studies support these findings, linking religiosity as antecedents of an attitude promoting FFs’ environmental intention (Singh et al. 2021 ) and chairpersons’ collectivist-shaped background to increased CSR activities in China (Luo et al. 2024 ).

Three quantitative studies have found that individual managers’ attitudes, similar to religious beliefs, foster ESG activities and performance. FF managers prioritize non-financial over financial gains from ESG activities, influenced by their positive attitude toward the community and higher levels of social identification (Fitzgerald et al. 2010 ; Mueller and Flickinger 2021 ). This results in FF managers contributing more financial and personal resources to their communities (Fitzgerald et al. 2010 ). Regardless, FF managers can exhibit attitudes that are different from those of non-FFs managers, resulting in heterogeneous business strategies (Lewis et al. 2015 ).

Two quantitative studies identified individual managers’ character traits as determinants of FFs’ ESG activities and performance. Overconfident managers boost CSR performance in FFs due to the perceived reputational benefits (Dick et al. 2021 ). CEO narcissism affects the selection of CSR instruments, steering them towards peripheral rather than embedded CSR. However, family influence can mitigate this negative impact by prioritizing collective goals over individual ambitions (Chen et al. 2021 ). Overall, research from the individual subsystem agrees that FF managers are driven by intrinsic motivations rather than economic or financial reasons to invest in ESG.

4.2 Family subsystem

A total of 23 studies have examined the family subsystem, revealing the importance of SEW, family values, and generational involvement for FFs’ ESG activities and performance. Notably, SEW is the most frequently used theoretical perspective (n = 15). Heterogeneity studies (n = 15) outnumber comparative studies (n = 8), and three conceptual studies were published. This trend aligns with the argumentation that the family subsystem is crucial in transforming an “ordinary” firm into an FF (Pieper and Klein 2007 ; Gómez-Mejía et al. 2011 ; Berrone et al. 2012 ). However, the relatively small number of studies indicates opportunities to further explore the core of FF research.

Several studies investigate the effect of families’ SEW-related needs and goals to ESG activities and performance, yielding ambivalent findings. On the one hand, studies indicate that, in general, SEW-related goals in FFs positively influence ESG activities and performance, enhancing reputation, and legitimacy (e.g., Bammens and Hünermund 2020 ; Ernst et al. 2022 ; Saeed et al. 2023 ). Hence, high trust and SEW, but low conflict levels, foster environmental and social strategies in FFs (Nikolakis et al. 2022 ). Individual SEW dimensions such as identification, commitment, and power drive CSR and environmental efforts (Uhlaner et al. 2012 ; Marques et al. 2014 ; Arena and Michelon 2018 ; Dayan et al. 2019 ). Similarly, FFs with a strong long-term orientation often adopt sustainability strategies (Memili et al. 2018 ; Dou et al. 2019 ). Additionally, FFs with transgenerational control intentions are likelier to embrace green innovations (Delmas and Gergaud 2014 ; Bammens and Hünermund 2020 ). If the next generation is willing to take over, the duration of family involvement is positively related to donations (Dou et al. 2014 ). Another contribution point out differences between first- and second-generation FFs regarding their green innovation engagement, as second-generation leaders shift their focus from internal to external stakeholders and aim to renew the FF (Wu et al. 2024 ). FFs’ unique resources and capabilities, often referred to as “familiness”, also have a positive impact on their absorptive capacity, mediated by CSR activities (Pütz et al. 2023 ).

On the other hand, studies find that ESG activities can be hindered if they are not aligned with family’s SEW goals. A conceptual article suggests that FFs are more inclined to adopt an selective approach to CSR rather than a holistic one, prioritizing the protection of their SEW (Zientara 2017 ). The close bond between the family and the FF can also become a hindrance if family conflicts arise, reducing the likelihood of adopting environmental and social strategies (Nikolakis et al. 2022 ). Likewise, multi-generation control may negatively sustainability certifications, driven by the desire to control the FF and maintain their legacy and traditional ways of working (Richards et al. 2017 ). FFs prioritizing control and influence are also less likely to disclose environmental engagement as a way to protect their SEW (Arena and Michelon 2018 ). Further, FF identity can drive tax evasion when perceived performance is low, as prioritizing FF survival may take precedence over risk and reputation concerns (Eddleston and Mulki 2021 ). Hence, it is crucial for future research to gain deeper insights into the ambivalent impact of SEW—the core concept of FF research—on ESG activities. Researchers should aim to comprehensively understand which ESG dimensions align with families' SEW goals and which do not, and what factors influence this relationship, building on the following recent insights. Randerson ( 2022 ) introduces the concept of family business social responsibility, explaining FFs’ engagement in socially responsible activities based on whether the business, owners, or family is the determining stakeholder. Hsueh et al. ( 2023a ) provide related insights into the heterogeneity of SEW in FFs and its effect on their CSR strategy: forward-looking SEW leads to the formalization of FFs’ CSR strategy for dynasty renewal, while backward-looking SEW results in informal CSR strategies to maintain the current legacy.

Two studies identify other motivational factors: ecological and social considerations (Kallmuenzer et al. 2018 ), market-related ambitions, and compliance with ethical and legal requirements (Déniz and Suárez 2005 ) foster CSR engagement, as FFs aim to remain competitive and secure their future survival. Family values also influence the willingness to pursue ESG-related strategies (Sharma and Sharma 2011 ). For example, FFs run by charitable families with high levels of foundation giving engage in more community-related CSR activities (Cruz et al. 2024 ).

4.3 Ownership subsystem

The most researched subsystem in this review, with a total of 34 studies, is the ownership subsystem. These studies analyze the effect of family ownership on various ESG activities compared to other ownership types. Two key observations emerge: First, almost all studies are comparative, focusing on FFs versus non-FFs, as varying levels of family ownership among FFs yield fewer insights. Second, the ownership subsystem exclusively uses quantitative methods, typically measuring family ownership with large secondary databases. Researchers assume that FFs’ SEW and their distinctive goals led to the observed outcomes without factually measuring these (Dyer and Whetten 2006 ; De Massis et al. 2014 ; Miller and Le Breton–Miller 2014 ). Some researchers have critiqued this approach, noting that the level of family ownership is an imprecise proxy for FFs’ goals (Berrone et al. 2012 ), suggesting an opportunity for more nuanced future research methodologies.

First, studies on overall ESG performance provide inconclusive results regarding whether family ownership has a positive or negative impact. Some studies suggest that family ownership fosters strengths or reduces concerns (Dyer and Whetten 2006 ; McGuire et al. 2012 ; Block and Wagner 2014 ; Cordeiro et al. 2018 ; Lamb and Butler 2018 ; Herrero et al. 2024 ; Rivera-Franco et al. 2024 ). Others indicate the opposite effect (Cruz et al. 2014 ; Rees and Rodionova 2015 ; El Ghoul et al. 2016 ; Labelle et al. 2018 ; Beji et al. 2021 ; Ahmed et al. 2024 ). Two main lines of argument are most prevalent: On the one hand, SEW can serve as a source of inspiration, and the goal of building strong ties with stakeholders and ensuring survival encourages FFs to invest in ESG (e.g., Lamb and Butler 2018 ). On the other hand, SEW can also be a restriction, and FFs shy away from ESG topics due to strategic and financial considerations, prioritizing family interests over non-family stakeholders (e.g., Labelle et al. 2018 ). Besides, family ownership is negatively related to organizational wrongdoing (Smulowitz et al. 2023 ) and positively to CSR legitimacy (Panwar et al. 2014 ). Notably, studies with U.S.-American samples generally report positive effects (e.g., Block and Wagner 2014 ), while cross-country studies find a negative effect (e.g., Rees and Rodionova 2015 ). European (e.g., Herrero et al. 2024 ) and Asian (e.g., El Ghoul et al. 2016 ) samples do not provide a consistent picture. In addition, studies that utilize the KLD database often find positive effects (e.g., Lamb and Butler 2018 ), whereas the remaining studies employ a variety of CSR databases (e.g., Cruz et al. 2014 ), which may contribute to the inconclusiveness of findings. Hence, other unidentified explanatory or moderating variables, along with the lack of standardized methods for measuring key variables, represent opportunities for future research.

Second, regarding environmental performance and green innovation, the findings are also mixed, indicating potential for future research. Researchers in favor of a positive influence assume that FFs, unlike non-FFs, have a greater interest in being perceived as responsible, protect their ecological environment, and are willing to take financial investments in the light of institutional pressures (Dyer and Whetten 2006 ; Berrone et al. 2010 , 2023 ; Block and Wagner 2014 ; Ardito et al. 2019 ; Dou et al. 2019 ; Horbach et al. 2023 ; Lorenzen et al. 2024 ). However, other researchers reason that FFs are too risk averse in fear of losing SEW and not flexible enough internally to invest in novel technologies, leading to a negative influence of family ownership on environmental performance compared to non-FFs (Rees and Rodionova 2015 ; Dal Maso et al. 2020 ; Miroshnychenko et al. 2022 ; Miroshnychenko and De Massis 2022 ) or a negative moderating effect of family ownership in the presence of institutional investors (Wu et al. 2023 ). One contribution can attribute almost half of the negative effect of family ownership on environmental performance to a lack of investments in training and development in FFs (Dal Maso et al. 2020 ). Following a more nuanced approach, Lorenzen et al. ( 2024 ) find in their meta-analysis that FFs have a lower footprint than non-FFs but do not differ regarding their handprint. The variability in measurement methods, such as ESG ratings (Dal Maso et al. 2020 ) and patent citations (Ardito et al. 2019 ), potentially contribute to these inconclusive findings and offer opportunities for future research.

Third, FFs are generally associated with more social strengths and less social concerns, including employee-friendly policies (Dyer and Whetten 2006 ; Bingham et al. 2011 ; Block and Wagner 2014 ; Kang and Kim 2020 ; Sahasranamam et al. 2020 ; Herrero et al. 2024 ). They argue that FFs aim to protect their SEW by forming close bonds to their stakeholders and supporting them. Further, family ownership leads to fewer layoffs of employees (Stavrou et al. 2007 ; Block 2010 ; Kim et al. 2020 ), as family managers identify strongly with the FF and are more concerned about protecting its reputation.

Fourth, the impact of family ownership on governance activities depends on the specific governance topic of analysis. Family ownership is linked to lower disclosure quantity and credibility, as disclosure of information contradicts FF goals of protecting SEW and maintaining the information asymmetry with other stakeholders (Blodgett et al. 2011 ; Campopiano and De Massis 2015 ; Hsueh 2018 ). However, one contribution finds a U-shaped relationship between family control and environmental performance disclosure, arguing that the reputational benefits outweigh the potential control loss when the family has extensive control over the firm (Terlaak et al. 2018 ). Adding a contextual pressure factor to this relationship, Zamir and Saeed ( 2020 ) show that FFs closer to financial centers are more willing to disclose information about their CSR activities. Only a few studies have focused on other governance dimensions, suggesting a need for future research: FFs are less likely to engage in tax avoidance strategies, valuing long-term reputation over short-term gains (Temouri et al. 2022 ). Regarding board compensation, family ownership negatively impacts CEO compensation, with family CEOs being paid less than professional CEOs in FFs (Croci et al. 2012 ).

4.4 Management subsystem

In this review, 12 studies focus on variables within the management subsystem to identify determinants of FFs’ ESG activities and performance. Most research has explored the effect of family involvement on boards and management, particularly the roles of family CEOs, as well as board characteristics such as diversity and independence. Three specific aspects of the research in this subsystem stand out. First, only quantitative studies have investigated the management subsystem, likely because board composition can be effectively measured using secondary databases. Second, many studies have included variables from both the management and ownership subsystems, examining the impact of board composition and characteristics across various types of ownership. Third, all but one article of this subsystem are underpinned by a theoretical framework, including agency theory (e.g., Jiang et al. 2023 ), stakeholder theory (e.g., Nadeem et al. 2020 ). The relatively conclusive results may be attributed to its solid theoretical foundation and can serve as a guide for future research on other subsystems.

Greater levels of family control via board involvement and family CEOs positively impact CSR practices (Cui et al. 2018 ; Meier and Schier 2021 ), philanthropy (Jiang et al. 2023 ), and pollution prevention (Chen et al. 2022 ). This relationship holds regardless of whether management variables are considered as a direct influence in a subset of FFs or as moderating variables that interact with family ownership. However, increased family involvement can also heighten SEW concerns regarding CSR disclosure, as families may hesitate to share information with external stakeholders, exacerbating feelings of losing control (Muttakin et al. 2018 ). Similarly, the negative effect on tax aggressiveness is stronger for founders with high control compared to later generations or hired CEOs due to their greater FF attachment (Brune et al. 2019 ). These findings may also inform future research on the ownership subsystem, helping to resolve inconclusive findings regarding specific ESG dimensions.

Board gender and age diversity generally promote ESG activities and performance in FFs. Researchers suggest that more diverse boards, particularly those with female directors, are more oriented towards stakeholder and reputation management. This diversity enhances CSR, improves disclosure, boosts environmental performance, and reduces tax aggressiveness (Cuadrado-Ballesteros et al. 2015 ; Cordeiro et al. 2020 ; Nadeem et al. 2020 ; Beji et al. 2021 ). Additionally, board capital and top management teams’ attention to environmental issues foster CSR disclosure and environmental performance in FFs (Kim et al. 2017 ; Muttakin et al. 2018 ). Likewise, directors chosen by non-family shareholders fosters FFs’ green innovation by contributing important resources and shift families’ attention to extended SEW (Du and Cao 2023 ).

4.5 Business subsystem

A total of 28 studies focus on the intersection of the business subsystem of FFs and their ESG activities and performance, making it the second most researched subsystem. Most studies analyze the effects of CSR performance, environmental activities, and disclosure on financial, stock market, and innovation outcomes, while non-economic outcomes like succession and strategy remain rather underexplored (cf. Gómez-Mejía et al. 2011 ). Two characteristics about this subsystem stand out: First, 21 out of the 28 studies analyze outcomes, with the business subsystem revolving around market-related outcomes and performance metrics. Future research could consider the business subsystem as a source of determinants for ESG activities. Second, this subsystem is the most atheoretical, common in finance-related outlets, seemingly without impacting the conclusiveness of findings.

Researchers predominantly agree that higher levels of ESG activities positively relate to FFs’ actual and perceived economic outcomes (Niehm et al. 2008 ; O'Boyle et al. 2010 ; Kang et al. 2015 ; Leonidou et al. 2023 ), which is amplified in FFs compared to non-FFs (Craig and Dibrell 2006 ; Singal 2014 ; Lartey et al. 2020 ; Yáñez-Araque et al. 2021 ; Yeon et al. 2021 ; Combs et al. 2023 ). They argue that FFs benefit from stronger ties to customers, suppliers, and public community, so that their ESG-related activities are perceived as more credible and amplify reciprocal responses (Combs et al. 2023 ). However, this relationship was not supported in all contexts, such as in Ghanaian SMEs (Adomako et al. 2019 ). Besides, FFs benefit from a protective effect, as outward-oriented CSR initiatives weaken the negative effect of R&D intensity on FF value in times of economic recession (Hu et al. 2023 ). FFs’ lack of diversity management does not negatively affect their financial performance if there is seemingly little connection to the prevailing culture in FFs (Singal and Gerde 2015 ). Similarly, as the distance between the family and the FF increases, such as in business groups, family ownership is negatively related to affiliated firms’ CSR (Oh et al. 2023 ).

Further, FFs better translate ESG activities into innovation than non-FFs, attributed to their organizational flexibility and long-term orientation (Craig and Dibrell 2006 ; Wagner 2010 ; Haddoud et al. 2021 ). Although FFs initially adopted a more risk-averse, long-term green innovation strategy in the early 2000s, they eventually caught up with non-FFs, demonstrating less volatility (Doluca et al. 2018 ). FFs also benefit more from transparency about their ESG activities compared to non-FFs (Nekhili et al. 2017 ; Maung et al. 2020 ; Sekerci et al. 2022 ), such as reducing costs of capital and debt (Gjergji et al. 2021 ; Duggal et al. 2024 ). Sekerci et al. ( 2022 ) attribute these findings to greater honesty, credibility, and expected responsible behavior, while investors suspect non-FFs of spreading dishonest news.

Only few studies have started to investigate business variables as determinants of ESG activities. Firm size influences CSR instrument selection (Graafland et al. 2003 ), while financial resources have an inverted U-shaped effect on CSR performance due to FFs’ alternative financial sources and normative CSR motivations (Tewari and Bhattacharya 2023 ). Professionalization has a positive impact on FFs' financial performance and sustainability reputation (Piyasinchai et al. 2024 ), and proactive CSR strategies and non-hierarchical CSR decision-making enhance non-family employees’ organizational identification (Hsueh et al. 2023b ). Marketing strategies show ambivalent relationships with sustainable performance in FFs (Battisti et al. 2023 ), hinting at a need for further research on the business subsystem as determinants.

4.6 Environment subsystem

A total of 20 studies investigate the environmental subsystem of FFs and its impact on their ESG activities and performance by examining the power balance between internal and external pressures as well as specific types of external pressures. Comparative studies (n = 15) outnumber heterogeneity studies (n = 5), suggesting a need for more research on the heterogeneity among FFs in this context. Three studies in the environmental subsystem utilize qualitative methods, indicating a potentially complex relationship between environmental factors and ESG topics in FFs (e.g., Dangelico et al. 2019 ).

First, researchers agree that FFs react differently to ESG pressures compared to non-FFs. The challenge for FFs lies in reconciling the diverse influences of internal and external stakeholders, as well as business-and family-related stakeholders, each with their own goals and expectations (Discua Cruz 2020 ). FFs prioritize internal stakeholders over external ones, balancing long-term SEW goals against the potential consequences of not complying with external influences (Dangelico et al. 2019 ; Abeysekera and Fernando 2020 ; García‐Sánchez et al. 2021 ).

Second, FFs adapt to external pressures from local communities (Dekker and Hasso 2016 ; Peake et al. 2017 ; Bammens and Hünermund 2023 ), external investors (Chen et al. 2010 ), institutional and public forces (Fritz et al. 2021 ; Wu et al. 2022 ; Ahmed et al. 2024 ). However, the effects are ambiguous, suggesting opportunities for further research. Some studies suggest that FFs self-regulate due to strong internal governance and higher self-motivation, reducing the impact of new regulations compared to non-FFs (Ding et al. 2016 , 2022 ; Peake et al. 2017 ; Bendell 2022 ). For instance, FFs invest in environmental innovation in anticipation of stricter regulations (Bendell 2022 ), commit less bribery in weaker macro-governance environment compared to non-FFs (Ding et al. 2016 ), and lay off fewer employees in regions with low population due to negative reputation concerns (Kim et al. 2020 ). However, other studies argue that external control mechanisms are crucial for improving FFs’ environmental performance, as they find that regulatory stringency and market competitiveness mitigate agency problems in FFs (Yu et al. 2021 ). Additionally, financial sanctions promote ESG investments to manage risk in Chinese FFs (Ahmed et al. 2024 ), and the one-child policy in China fosters CSR to facilitate intergenerational succession (Cumming et al. 2024 ). In line with this second argumentation, political connections can be leverages to reduce external control, leading to lower environmental orientation (Brumana et al. 2024 ) and increased misconduct and bribery (Du 2015 ; Jiang and Min 2023 ).

5 Discussion

5.1 future research opportunities.

This literature review has uncovered potential areas for future research, as illustrated in Fig.  2 . To address gaps and narrow investigations in the field, researchers are encouraged to adopt a more nuanced and holistic approach. Future research directions are categorized using the same matrix employed in the findings. Research avenues across the three categories can and should be combined to advance FF ESG research. Specifically, methodical approaches should be prioritized initially, as refining these methods can provide a solid foundation for exploring other research avenues and significantly progress the field of FF ESG research.

5.1.1 Future research opportunities of first priority on FF subsystems

Future research avenue 1—Intersection of family, management, and ownership subsystems. FF research has established that only the presence of both ability and willingness can result in FF-particularistic behavior (De Massis et al. 2014 ), i.e., combination of family, business, and ownership subsystem, and has predominantly focused on SEW preservation as FFs’ main goal (Gómez-Mejía et al. 2011 ). However, studies frequently use broad measures of family ownership or involvement in management to infer FF goals, potentially misattributing outcomes to SEW preservation (Berrone et al. 2012 ; Miller and Le Breton-Miller 2014 ). This rather vague approach may explain the inconsistent findings related to family ownership and ESG performance. To address these gaps, future research should delve into the following areas: First, researchers may investigate how the ability dimension in FFs, i.e., family ownership and management involvement, has been measured and how each subdimension of ability impacts ESG activities and performance (Miroshnychenko et al. 2022 ). For instance, Block ( 2010 ) finds varying effects of family ownership versus management involvement on downsizing, highlighting the need for more precise measurement. Second, research could benefit from examining the interplay among various SEW dimensions to understand their combined effect on ESG performance. Therefore, researchers may explore how SEW dimensions influence ESG activities and assess whether FFs and non-FFs pursue similar ESG goals, drawing on recent heterogeneity studies from the family subsystem. These studies have tried to capture the unique dynamics among various FF subsystems and provide initial starting points as to which dimensions are relevant, such as long-term orientation (Dou et al. 2019 ), reputation motives (Bammens and Hünermund 2020 ), trust and conflict among family members (Nikolakis et al. 2022 ), and dynastic renewal and identification (Hsueh et al. 2023a ). Moreover, Randerson ( 2022 ) provides a conceptual basis to integrate SEW and familiness into FF ESG research. To enhance understanding, researchers should prioritize survey-based approaches that directly measure FFs’ ability and willingness to engage in ESG initiatives. As measuring FF and non-FF goals more precisely bears challenges, researchers should start with a rigorous analysis of previous research to find the most fitting scale or way of measuring goals based on their specific research questions and hypotheses (e.g., Prügl 2019 ). Despite the additional effort required, such approaches will provide deeper insights and clarify the complex interactions between family, management, and ownership subsystems in relation to ESG performance. Third, researcher may include relevant moderating and mediating factors, as only few studies analyze such variables beyond family control measures, despite previous suggestions from researchers that FF behavior is likely influenced by a multitude of moderating and mediating factors (De Massis et al. 2014 ). Examples include long-term orientation (Memili et al. 2018 ), normative motivation (Ernst et al. 2022 ), and the use of the family name as the FF name (Cruz et al. 2024 ). Thus, these are exemplary unaddressed questions for future research on family control and goals related to ESG performance: Are current measurement methods capturing the nuanced effects of family control? Do FFs and non-FFs pursue similar goals with ESG engagement? Do FFs differ among each other regarding their SEW preservation goals which, in turn, affects their ESG activities? Which SEW dimensions have the most significant impact on ESG performance? Are there specific SEW aspects that enhance or hinder ESG outcomes? Are there interdependencies among SEW dimensions? What other family-related variables are relevant to understand FFs’ ESG activities? Which level of family influence benefits ESG performance most, which hinders most? How do FFs and non-FFs differ with regard to their ability and willingness to invest in ESG activities?

Future research avenue 2—FF heterogeneity. In this review, 69% of all studies compare FFs and non-FFs, predominantly treating FFs as a homogeneous group. However, this view has been challenged in FF research in recent years (De Massis et al. 2014 ; Daspit et al. 2021 ). Researchers advocate for further investigation into FF heterogeneity (Calabrò et al. 2019 ), a need that has also become evident concerning the individual and environmental subsystems. Studies with FF samples find significant differences in their ESG performance and outcomes, suggesting that treating them as a single category may overlook critical differences in ESG performance and strategies (e.g., Chen et al. 2010 ; Berrone et al. 2023 ). Although FF heterogeneity studies have gained momentum in recent years, with 21 out of 39 such studies in this review published since 2021, conceptual and qualitative approaches, such as in-depth case studies, are needed to foster our understanding. Such studies enable researchers to identify and reveal variations among FFs, distinguish between different archetypes of FFs in terms of their ESG approaches, and identify key variables that differentiate FFs. Researchers can draw on the findings and methodologies from studies by Discua Cruz ( 2020 ), Marques et al. ( 2014 ), Bhatnagar et al. ( 2020 ), and Hsueh et al. ( 2023a ). These studies have leveraged non-quantitative approaches to examine underlying motives and relationships within FFs regarding their ESG reporting, CSR engagement, philanthropy, and non-family employees’ organizational identification. For instance, researchers can analyze how FFs’ familiness impact their ESG performance (Pütz et al. 2023 ), which has rarely been the focus of studies. Researchers may also examine how the generational life cycle stage of FFs affects their ESG activities and performance, as this aspect is crucial as it may influence strategic decisions and long-term sustainability (Wu et al. 2024 ). Afterwards, scholars could revisit the comparison between FFs’ and non-FFs’ ESG performance, trying to solve mixed and inconclusive findings in comparative studies by incorporating a broader range of variables that have been found to explain differences among FFs. Exemplary unanswered research questions are: Why do FFs differ regarding their ESG performance? What role do their individual managers’ attitudes and character traits, resources, history, processes, goals, or local environment play to explain the differences in their determinants and outcomes of ESG performance? Are there differences in terms of the individual ESG dimensions? Have these factors changed over time in FFs? Are there noticeable differences in ESG approaches between first-generation and multi-generational FFs? Do specific attributes of familiness drive better or worse ESG outcomes?

5.1.2 Future research opportunities of first priority on ESG dimensions

Future research avenue 3—ESG measurement and greenwashing. More than half of all reviewed studies rely on CSR or ESG databases that collect and accumulate self-reported firm data. This approach warrants reconsideration for two main reasons as indicated in the subchapter regarding the ownership subsystem. First, different ESG databases or rating agencies apply varying definitions and standards when calculating ESG performance. The same FF can actually achieve opposite results depending on the source, which not only harms comparability between studies but also affects the validity of effect sizes, resulting in inconclusive findings across studies (Billio et al. 2021 ). Second, current research relies mainly on ESG data based on self-reported firm disclosures. However, ESG performance in particular is a topic where the risk of data bias due to social desirability is very high so that firms may exaggerate their positive ESG traits while downplaying negative ones (Nederhof 1985 ; Arvidsson and Dumay 2022 ). Hence, future research would benefit from more objective and comparable ESG indicators, such as the actual level of emissions, as demonstrated by Berrone et al. ( 2010 ) who used weighted on-site emissions to assess environmental performance. In addition, meta-analytical studies can help to clarify the impact of ESG measurement on the significance of determinants and outcomes. An interesting approach is also shown by Lorenzen et al. ( 2024 ), as they differentiate between ecological footprint and handprint in their meta-analysis, providing a more nuanced pictures of FFs’ environmental performance. In addition, researchers may also investigate greenwashing behaviors among FFs. For instance, Kim et al. ( 2017 ) find a higher tendency of greenwashing for non-FFs than FFs arguably due to their desire to preserve their SEW. I suggest fellow scholars to choose similar approaches to extend knowledge on this topic. Hence, I propose the following exemplary research questions: How do more objective ESG measurements relate to ESG ratings? Do determinants and outcomes vary based on the measurement of ESG variables? Are actual and perceived ESG performance correlated in FFs? Is there a stronger or weaker correlation compared to non-FFs? Do FFs exhibit a stronger tendency to adjust their reported ESG performance due to social desirability pressures? How do contextual factors, such as current financial performance, influence greenwashing behavior in FFs? Which goals, such as transgenerational intentions and reputation, impact FFs’ greenwashing behavior?

5.1.3 Future research opportunities of second priority on FF subsystems

Future research avenue 4—Moderating effects within the ownership subsystem. Future research should more thoroughly examine firm-, industry-, and country-level differences to explain the mixed results seen in comparative studies, particularly within the ownership subsystem. Initial studies hint at the importance of accounting for country-level differences to acknowledge the varying influences of governmental or regulatory environments, culture, and society’s norms on FFs’ ESG performance (e.g., Rees and Rodionova 2015 ; Miroshnychenko and De Massis 2022 ). The comparison of findings among the comparative studies indicates a relevant influence of the sample firms’ origin, since most studies with a positive relationship of family control on ESG have analyzed U.S. or other one-country-samples (e.g., Cui et al. 2018 ), whereas studies with partially contradicting results have relied on Asian or global samples (e.g., El Ghoul et al. 2016 ). In addition, scholars should also gain a more nuanced understanding about how firm characteristics and industry influences the ESG performance of FFs. For example, Terlaak et al. ( 2018 ) find a moderating effect of heavily polluting industries, Battisti et al. ( 2023 ) highlight the importance of advertising intensity, and Piyasinchai et al. ( 2024 ) emphasize the role professional management practices. The specific industry of FFs can affect their pressures, goals, and resources which is why future research would benefit from investigating firm- and industry-level differences. Researchers may also rely on Gómez-Mejía et al. ( 2011 ) who argue why and how FFs differ from non-FFs in five categories of managerial decisions and firm characteristics. Moreover, future studies can build upon the insights provided by Lorenzen et al. ( 2024 ), whose meta-analysis demonstrates that the effect of FF status on environmental performance differs for large and listed firms compared to small- and medium-sized firms. In addition, Bammens and Hünermund ( 2020 ) argue that listed FFs may prioritize short-term goals due to the greater distance between family and firm, contrasting with privately held FFs that are more focused on long-term objectives, in comparison to findings by Rees and Rodionova ( 2015 ). Thus, future research would benefit from either conducting meta-analyses or analyzing large global samples that can account for different business types, industries, and origins of firms. Building upon these first insights, additional research questions arise, such as: What are the key factors that distinguish countries where FFs exhibit varying ESG performance? Which industries excel in ESG performance, and how do they compare to others? Are non-FFs more affected by their industry than FFs? Do listed FFs show lower ESG performance across all dimensions or just specific ones? Do listed FFs act more like non-FFs than private FFs? What firm characteristics unique to FFs impact their ESG activities?

Future research avenue 5—Individual subsystem. Until now, the effect of individual FF manager attitudes and character traits on FF ESG activities and performance has received rather little attention in research. Future research can transfer and extend both the established theoretical foundation, the initial findings from FF ESG research, and CEO research. First, upper echelons theory by Hambrick and Mason ( 1984 ) proposes that managers’ experiences, values, and personalities have a high influence on their business choices and is a key theory in strategic management research. This theory offers a great fundamental basis for FF ESG research to deduce hypotheses, as research on the effect of CEOs on their firms’ actions and performance demonstrates (Wang et al. 2016 ). Second, both first quantitative and conceptual insights highlight that these individual influences are key determinants to understand why FFs engage in enhancing their ESG performance (e.g., Singh et al. 2021 ). Researchers could build on and empirically test the hypotheses by Le Breton-Miller and Miller ( 2016 ), proposing that FFs are more engaged in sustainable practices when FF owners and managers are influenced by religious values and their parents and educational background convey the importance of discipline and commitment to the FF and society. It would be highly relevant for future research to analyze whether this effect is potentially amplified in FFs due to the high levels of personalized control (Sharma and Sharma 2011 ). Third, existent research on CEO characteristics demonstrates the plethora of family manager and owner characteristics that may also be relevant for their decision-making in FFs. Compared to the state of research for CEOs, the knowledge about the individual FF manager or owner as key decision makers for ESG behaviors in FFs is still quite limited. Thus, FF researchers may draw on research by Kaplan et al. ( 2012 ), Manner ( 2010 ), and Barker and Mueller ( 2002 ) to identify relevant determinants from the individual subsystem, such as educational background, career experience, interpersonal or execution skills, tenure. For example, Cumming et al. ( 2024 ) find moderating effects of highly personal owner characteristics, such as number of children, number of sons, and surpassing of reproductive age, on the effect of one-child policy introduction on CSR performance. Similarly, Du and Cao ( 2023 ) show a positive effect of green professional backgrounds of directors on green innovation in FFs. Exemplary unanswered research questions are the following: How do FF managers’ attitudes, beliefs, and character traits influence their decisions regarding ESG engagement? Do family members exhibit different values and attitudes towards the environment and society than non-family members in FFs? How do individual differences, such as values or educational backgrounds, between preceding generations and successors impact FF ESG performance? Are younger family members more likely to foster the engagement in ESG practices? Do FF managers’ attitudes and beliefs moderate the influence of FF control and goals on ESG engagement?

Future research avenue 6—Business subsystem. Current research has primarily explored how ESG engagement impacts the financial performance of FFs, focusing on the “CSR-CFP relationship”. Future studies should investigate how ESG activities affect critical non-financial goals in FFs, which can offer a more holistic view of the benefits and challenges associated with ESG behaviors. For example, interdependencies between FFs’ SEW and ESG activities could be a valuable area of study, as ESG initiatives may enhance FFs’ SEW by improving the next generation’s willingness to take over (Dou et al. 2014 ) or increasing non-family employees’ organizational identification (Hsueh et al. 2023b ). Exploring these dynamics could provide insights into how ESG efforts contribute to both financial and non-financial outcomes. Moreover, future studies would benefit from adopting a different perspective and analyzing FF business variables, especially financial performance, as determinants of ESG performance for two reasons. First, financial resources are essential for any firm to invest in ESG issues, as payback periods are typically longer and the prospects for success unclear. For instance, green innovation is considered to be significantly more financially intensive than general innovation (e.g., Holzner and Wagner 2022 ). Research by Miroshnychenko and De Massis ( 2022 ) highlights that cash reserves, net sales growth, and firm size significantly influence the likelihood of adopting sustainability practices. However, non-financial business variables, such as professional management practices and dynamic capabilities, can also enhance FFs’ ESG strategy, reputation, and financial performance (Leonidou et al. 2023 ; Piyasinchai et al. 2024 ). Second, FFs have unique financial structures compared to non-FFs, which is likely to influence their financial flexibility for ESG engagement. Sirmon and Hitt ( 2003 ) argue that FFs possess patient financial capital that is invested with a long-term commitment and allows FFs to pursue more innovative strategies than non-FFs. Tewari and Bhattacharya ( 2023 ) provide first empirical support, showing that the impact of financial resources on CSR activities differs between FFs and non-FFs. However, they also acknowledge that FFs have less access to external capital due to their control aspirations and smaller firm size. Based on these studies the importance of firm performance as a determinant of ESG performance in FFs needs further investigation. Exemplary research questions are as follows: How do ESG activities and performance impact FFs’ non-financial performance? Which dimensions of FF performance influence ESG investments? What technical and management capabilities foster ESG activities in FFs? Does FF performance affect different ESG dimensions similarly? How does this compare to non-FFs? What role does the expected financial performance play? How does the FF life cycle affect the relationship of FF financial performance to ESG investments? For example, are founder-led FFs more conservative than FFs at a later generational stage? Are FFs willing to give up control to raise external capital for ESG investments? How do ESG activities serve as a risk management or value protection tools in terms of financial or reputational distress?

Future research avenue 7—Environment subsystem. The current understanding of how environmental factors and stakeholders influence FFs’ ESG performance is still limited and requires deeper exploration. First, the impact of climate change as a pressure on FFs is an underexplored area. A study by Wright and Nyberg ( 2017 ) shows that firms normalize and downplay the big challenge of climate change, with their environmental engagement diminishing over time. Future research could analyze this phenomenon among FFs, since their higher level of long-term orientation and local embeddedness (e.g., Berrone et al. 2010 ; Memili et al. 2018 ) might counteract this reaction. Thus, tangible climate change consequences in their immediate environment could foster ESG performance improvements. For example, Horbach et al. ( 2023 ) demonstrate that extreme weather events promote firms’ level of greenness. Second, given recent energy and environmental policy developments, the impact of regulatory and governmental influences on FFs’ behaviors offers opportunities for further investigation with great practical impact for FF owners and managers. First studies detect a self-regulatory approach of FFs (e.g., Bendell 2022 ), but many potential determinants of the relationship between regulatory pressure and ESG investments have not been investigated yet. For instance, Amore and Minichilli ( 2018 ) find that FFs show greater investment resilience under local political uncertainty. Bammens and Hünermund ( 2023 ) introduce a strong ecological community logic as a fostering condition for green innovation, but the reverse influence and effect have not been investigated yet. Future research should examine how similar environmental context factors influence ESG activities, particularly considering FFs’ place-based culture (e.g., Kim et al. 2020 ; Bammens and Hünermund 2023 ). Third, future research would benefit from analyzing more comprehensive models and including variables from other FF subsystems. For example, FF governance could be a relevant factor, as female managers are considered to be more stakeholder-oriented (e.g., Cordeiro et al. 2020 ) and non-family managers to be less focused on SEW goals and FF reputation (e.g., El Ghoul et al. 2016 ). Hence, a higher share of female managers/non-family manager could amplify/weaken the effect of regulatory pressure. Cumming et al. ( 2024 ) find that individual owner characteristics significantly moderate policy responses due to the highly personalized control in FFs. Other variables that have an influence on ESG-related behavior, such as FFs’ transgenerational control intentions (e.g., Bammens and Hünermund 2020 ) or political connectedness (e.g., Du 2015 ), might also moderate or mediate the effects of regulatory pressures. These factors should be considered in future studies to incorporate the uniqueness of FFs and their goals in their response to regulatory pressures. Hence, some unanswered research questions are the following: How does climate change impact the environmental performance of FFs compared to non-FFs? More or less than for non-FFs? Are local versus distant environmental disasters experienced differently in terms of impact and response by FFs? How do FFs differ regarding their reaction to regulatory pressure regarding ESG topics, e.g., self-regulatory versus reactive? What role do FF employees play in shaping their firms’ ESG activities, and how is this influenced by the level of ESG community logic? Does FF governance affect the impact of regulatory pressure on ESG performance? Are FFs pursuing different goals in their strategy to deal with regulatory pressures related to ESG issues?

5.1.4 Future research opportunities of second priority on ESG dimensions

Future research avenue 8—ESG heterogeneity. Research on ESG heterogeneity is crucial, as aggregated ESG and CSR metrics often present inconsistent results, which mask the nuanced approaches of FFs. Quantitative analyses of overarching ESG metrics can be misleading, failing to capture the complexity of FFs’ ESG practices, as findings are more conclusive when comparing results for each subtopic. For instance, Block and Wagner ( 2014 ) highlight that FFs may simultaneously act responsibly and irresponsibly, with varying engagement levels across different ESG dimensions. They find that family ownership positively influences environmental and product-related ESG performance but negatively impacts community-related performance. This nuanced approach has partially been overlooked, with research often focusing primarily on environmental issues or general ESG performance. Future research could understand FF behavior in a more granular way by acknowledging the complexity and heterogeneity of ESG. For instance, Lorenzen et al. ( 2024 ) suggest distinguishing between detailed aspects of environmental performance, such as handprint and footprint, to gain deeper insights. By building on studies such as Croci et al. ( 2012 ), Bingham et al. ( 2011 ), or Kang and Kim ( 2020 ), researchers should integrate more variables measuring the governance and social dimensions, such as human and employee rights, diversity, compensation and competition fairness, and transparent communication. Potential research questions to answer for future studies include the following: Which ESG dimensions are particularly aligned with which FF goals? Do particular family members, such as women or later generations, prioritize certain ESG issues differently? How have FFs' ESG preferences changed over time? Are FFs more effective than non-FFs on social issues aligned with their SEW goals, and less effective on unrelated issues? Why might some FFs exhibit behavior similar to non-FFs in governance-related topics?

5.2 Practical implications

This article also provides important practical insights for managers and stakeholders of FFs who aim to gain a deeper understanding about FFs’ ESG performance. By increasing awareness of the factors influencing FFs’ ESG performance and the potential outcomes, FF owners and managers can more effectively design their firm’s individual ESG strategy. This understanding also helps them anticipate potential obstacles and the effects of their actions. Given that the family is often also the largest shareholder and has an interest in the firms’ longevity, it is crucial for FFs to comply with the latest ESG regulations and to understand their firms’ future ESG readiness. Understanding ESG performance helps FFs to identify risks that could affect their survival. Effective management of these risks can protect the firm from potential financial, legal, and reputational damage, which is especially important for family members.

Additionally, investors and financial institutions are increasingly prioritizing ESG factors when making decisions. FFs that demonstrate strong ESG performance are more likely to attract investment from socially conscious investors and funds that prioritize sustainability alongside financial returns, aligning with their strategic approach and cultural values. Superior ESG performance can be a strong value proposition for FFs, attracting customers, employees, and business partners who value sustainability and ethical business practices. A future-ready and sustainability-oriented FF may also be more attractive for the next generation, supporting the long-term survival of the FF and family control over it. Furthermore, stakeholders from market, politics, and government may prefer future-proof and compliant FFs as suppliers or customers or feel inclined to shape effective ESG initiatives or subsidies for FFs.

5.3 Limitations

As with all research, this literature review has few limitations. The first limitation is the potential oversight of influences stemming from variations in the samples used, such as whether FFs are private or public, their country of origin, or the industry in which they operate. Analyzing how these factors impact ESG performance was beyond the purpose and scope of this review. The second limitation is the inability to distinguish between effects based on how ESG performance was measured. The exact measurement of certain FF variables, such as family control as a dummy or a metrical variable including ownership and/or management involvement, is particularly difficult to consider. Since several studies use different measurement approaches for family control (e.g., family ownership or management involvement), future meta-analyses or sensitivity studies should explore these variations and their impact on results (e.g., Miroshnychenko et al. 2022 ). Finally, the article selection and analysis process are inherently subjective. To mitigate this, I adhered to a systematic approach and meticulously documented each step, aiming to reduce any bias (Webster and Watson 2002 ; Wolfswinkel et al. 2013 ).

6 Conclusion

ESG-related FF research has continuously grown in both quantity and importance over the past two decades and will remain a central topic for researchers and practitioners. To support and steer future research, this literature review structures and synthesizes the current body of knowledge at the intersection of FF and ESG research, providing a comprehensive understanding of how various ESG dimensions impact different FF subsystems. By identifying and structuring new research avenues, this review supports the advancement of the field and enriches both FF and ESG research.

Availability of data and material

I do not analyze or generate any datasets, because my work is based on a literature reviewing approach. All reviewed studies are included in this article.

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• J Can Acad Child Adolesc Psychiatry
• v.20(1); 2011 Feb

Systematic Reviews and Meta-Analyses

Lindsay s. uman.

1 Clinical Psychologist, IWK Health Centre, Halifax, Nova Scotia

With an ever-increasing plethora of studies being published in the health sciences, it is challenging if not impossible for busy clinicians and researchers alike to keep up with the literature. Reviews summarizing the outcomes of various intervention trials are therefore an extremely efficient method for obtaining the “bottom line” about what works and what doesn’t.

Key Terms Defined

Systematic reviews differ from traditional narrative reviews in several ways. Narrative reviews tend to be mainly descriptive, do not involve a systematic search of the literature, and thereby often focus on a subset of studies in an area chosen based on availability or author selection. Thus narrative reviews while informative, can often include an element of selection bias. They can also be confusing at times, particularly if similar studies have diverging results and conclusions. Systematic reviews, as the name implies, typically involve a detailed and comprehensive plan and search strategy derived a priori, with the goal of reducing bias by identifying, appraising, and synthesizing all relevant studies on a particular topic. Often, systematic reviews include a meta-analysis component which involves using statistical techniques to synthesize the data from several studies into a single quantitative estimate or summary effect size (Petticrew & Roberts, 2006). In contrast to traditional hypothesis testing which can give us information about statistical significance (i.e., did the intervention group differ from the control group) but not necessarily clinical significance (i.e., was this difference clinically meaningful or large), effect sizes measure the strength of the relationship between two variables, thereby providing information about the magnitude of the intervention effect (i.e., small, medium, or large). The type of effect size calculated generally depends on the type of outcome and intervention being examined as well as the data available from the published trials; however, some common examples include odds ratios (OR), weighted/standardized mean differences (WMD, SMD), and relative risk or risk ratios (RR). Although systematic reviews are published in academic forums, there are also organizations and databases specifically developed to promote and disseminate them. For example, the Cochrane Collaboration ( www.cochrane.org ) is a widely recognized and respected international and not-for-profit organization that promotes, supports, and disseminates systematic reviews and meta-analyses on the efficacy of interventions in the health care field.

8 Stages of a Systematic Review and Meta Analysis

1. formulate the review question.

The first stage involves defining the review question, forming hypotheses, and developing a review title. It is often best to keep titles as short and descriptive as possible, by using the following formula: Intervention for population with condition (e.g., Dialectical behavior therapy for adolescent females with borderline personality disorder). Reviews published with the Cochrane Collaboration do not need to be identified as such, but reviews published in other sources should also indicate in the title that they represent a systematic review and/or meta-analysis. If authors chose to conduct their review through the Cochrane Collaboration, they will also be required to register their title to the appropriate review group, which in essence “saves their spot” for this topic and provides access to further Cochrane support (e.g., assistance running search strategies).

2. Define inclusion and exclusion criteria

The Cochrane acronym PICO (or PICOC) which stands for population, intervention, comparison, outcomes (and context) can be useful to ensure that one decides on all key components prior to starting the review. For example, authors need to decide a priori on their population age range, conditions, outcomes, and type(s) of interventions and control groups. It is also critical to operationally define what types of studies to include and exclude (e.g., randomized controlled trials-RCTs only, RCTs and quasi-experimental designs, qualitative research), the minimum number of participants in each group, published versus unpublished studies, and language restrictions. For Cochrane Reviews, this information gets prepared, peer-reviewed, and published in a Protocol format first, which is then replaced with the full Review once it is completed.

3. Develop search strategy and locate studies

This is the stage where a reference librarian can be extremely helpful in terms of helping to develop and run electronic searches. Generally, it is important to come up with a comprehensive list of key terms (i.e., “MeSH” terms) related to each component of PICOC to be able to identify all relevant trials in an area. For example, if the age range is 13–18 year old females, search terms may need to include any of the following: adolescents, teenagers, youth, female, women, girls, etc. The key in developing an optimal search strategy is to balance sensitivity (retrieving a high proportion of relevant studies) with specificity (retrieving a low proportion of irrelevant studies). Searches generally include several relevant electronic databases but can also include checking article reference lists, hand-searching key journals, posting requests on listservs, and personal communication with experts or key researchers in the field.

4. Select studies

Once a comprehensive list of abstracts has been retrieved and reviewed, any studies appearing to meet inclusion criteria would then be obtained and reviewed in full. This process of review is generally done by at least two reviewers to establish inter-rater reliability. It is recommended that authors keep a log of all reviewed studies with reasons for inclusion or exclusion, and it may be necessary to contract study authors to obtain missing information needed for data pooling (e.g., means, standard deviations). Translations may also be required.

5. Extract data

It can be helpful to create and use a simple data extraction form or table to organize the information extracted from each reviewed study (e.g., authors, publication year, number of participants, age range, study design, outcomes, included/excluded). Data extraction by at least two reviewers is important again for establishing inter-rater reliability and avoiding data entry errors.

6. Assess study quality

There has been a movement in recent years to better assess the quality of each RCT included in systematic reviews. Although there are brief check-lists available such as the 5-point Oxford Quality Rating Scale ( Jadad et al., 1996 ) commonly used in Cochrane reviews, this measure is heavily influenced by double-blinding which is appropriate for drug trials but generally not for psychological or non-pharmacological interventions. There are other more comprehensive recommended guidelines and standards available such as the Consolidated Standards of Reporting Trials (CONSORT Statement; http://www.consort-statement.org/ ), as well as articles providing recommendations for improving quality in RCTs and meta-analyses for psychological interventions (e.g., Uman et al., 2010 ).

7. Analyze and interpret results

There are various statistical programs available to calculate effects sizes for meta-analyses, such as the Review Manager (RevMan) program endorsed by the Cochrane Collaboration. Effect sizes are stated along with a 95 % confidence interval (CI) range, and presented in both quantitative format and graphical representation (e.g., forest plots). Forest plots visually depict each trial as a horizontal diamond shape with the middle representing the effect size (e.g., SMD) and the end points representing both ends of the CI. These diamonds are presented on a graph with a centre line representing the zero mark. Often the left side of the graph (< zero) represents the side favoring treatment, while the right side (> zero) represents the side favouring the control condition. At the bottom of the graph is a summary effect size or diamond representing all of the individual studies pooled together. Ideally, we would like to see this entire diamond (effect size and both anchors of the CI) falling below zero, indicating that the intervention is favoured over the control. In addition, most programs also calculate a heterogeneity value to indicate whether the individual studies are similar enough to compare. In this case, it is preferable to have non-significant findings for heterogeneity. It is still possible to pool studies when significant heterogeneity exists, although these results should be interpreted with caution or reasons for the heterogeneity should be explored. As with all papers, the last step in the writing process involves summarize the findings, and providing recommendations for clinical work (e.g., which interventions are efficacious, for whom, and under what conditions) and research (e.g., what areas/topics/interventions require further research.

8. Disseminate findings

Although reviews conducted through the Cochrane Collaboration get published in the online Cochrane Database of Systematic Reviews, they are often quite lengthy and detailed. Thus, it is also possible and encouraged to publish abbreviated versions of the review in other relevant academic journals, as long as they are clearly indicated as such (e.g., Uman et al., 2008 ). Plain language summaries for families and patients are also commonly provided, and there is an expectation that reviews should be regularly updated to ensure they are always up-to-date and relevant. Indeed, participating in a review update or joining a well-established review team, can be a helpful way of getting involved in the systematic review process.

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