A systematic review often comes hand in hand with a meta-analysis, but it’s important to note that not every systematic review includes one. While systematic reviews summarize the existing evidence, meta-analyses go further by statistically assessing that evidence, giving us deeper insights.
This article on meta-analysis is the third installment in the Understanding Literature Reviews in Healthcare series. Previously, we explored Narrative Reviews and Systematic Reviews.
Meta-Analysis
The term meta-analysis indicates a process that examines previous analyses. By combining research data from multiple studies, a well-conducted analysis provides a clearer and more reliable answer to important research questions. This method not only boosts statistical power but also improves our understanding of an intervention’s effectiveness beyond what a single study can offer.1
This article focuses on traditional meta-analyses. If you’re curious about network meta-analyses, visit this review guide by Sheldon L. Sirota, DO Memorial Library at Touro University.
Pros and Cons
Pros of Meta-Analysis
- Increased Statistical Power: Pooling data from multiple studies enhances the ability to detect true effects that individual studies might miss due to small sample sizes
- Improved Estimates of Effect Size: Pooling results yields more precise estimates of an intervention’s effectiveness or the association between variables
- Pattern and Relationship Identification: Can uncover trends across studies that individual studies might overlook
- Resolution of Conflicting Findings: When individual studies report contradictory results, can help reconcile these differences by providing an overall assessment.
- Generation of New Research Questions: By highlighting gaps or inconsistencies in the existing literature, meta-analyses suggest areas for future research1–3
Cons of Meta-Analysis
- Publication Bias: Studies with significant or positive results are more likely to be published, which can skew meta-analytic findings if unpublished studies with null results are excluded
- Heterogeneity: Variations in study designs, populations, interventions, and outcomes can complicate synthesizing results and may lead to misleading conclusions if not adequately addressed
- Quality of Included Studies: Only as reliable as its included studies; poor-quality research can undermine validity
- Complexity and Resources: Requires significant time, expertise, and resources
- Potential for Misleading Results: If not carefully executed, can produce overconfident conclusions, especially when studies have diverse methodologies or biases1–3
Methodology/Guidelines
Methodology
Because a meta-analysis typically goes hand in hand with a systematic review, we often find ourselves leaning on the same methodological sources..
- Section 4.3: Meta-Analysis from the JBI Manual for Evidence Synthesis: Covers statistical methods for synthesizing multiple study results
- Chapter 10: Analysing Data and Undertaking Meta-Analyses from the Cochrane Handbook for Systematic Reviews of Interventions: Guidance on analyzing data; highlights the importance of understanding data types, selecting suitable effect measures, and addressing heterogeneity
- Fixed or Random Effects Meta-Analysis? Common Methodological Issues in Systematic Reviews of Effectiveness: This JBI Evidence Implementation article by Tufanaru, Munn, Stephenson, and Aromataris discusses common methodological challenges and best practice
Protocols
The protocol is the written plan that will guide your meta-analysis. Registration is highly recommended and often required, just like for systematic reviews.
- A Practical Guide: Protocol Development for Systematic Reviews: This helpful guide from Covidence walks your team through each step of writing and registering your protocol.
- Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P): This checklist highlights 17 key items that are important for creating protocols; it is designed to support your team in developing a thorough and well-rounded protocol
- PRISMA-P 2015: Elaboration and Explanation: Shares a detailed overview of each item on the PRISMA-P checklist
Reporting Guidelines
Clear reporting is crucial for transparency and reproducibility. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist is a fantastic tool to ensure your methodology is clearly reported. Plus, many journals require a completed PRISMA checklist when you submit your meta-analysis.
- PRISMA 2020 Explanation and Elaboration: A detailed walkthrough of PRISMA reporting with examples
Assessment
In my overview of Systematic Reviews, I mentioned AMSTAR (A MeaSurement Tool to Assess systematic Reviews) 2. However, Russo’s article in Gastroenterology & Hepatology, How to Review a Meta-analysis, offers additional guidance in designing your meta-analysis.
Examples
Share your AMSTAR 2 ratings of the following meta-analyses in the comments.
- Li X, Li D. Cardiovascular adverse events associated with immune checkpoint inhibitors: a meta-analysis. Front Immunol. 2024 Jun 24;15:1394123. doi: 10.3389/fimmu.2024.1394123. PMID: 38979409; PMCID: PMC11228135.
- Sorin M, Prosty C, Ghaleb L, Nie K, Katergi K, Shahzad MH, Dubé LR, Atallah A, Swaby A, Dankner M, Crump T, Walsh LA, Fiset PO, Sepesi B, Forde PM, Cascone T, Provencio M, Spicer JD. Neoadjuvant Chemoimmunotherapy for NSCLC: A Systematic Review and Meta-Analysis. JAMA Oncol. 2024 May 1;10(5):621-633. doi: 10.1001/jamaoncol.2024.0057. PMID: 38512301; PMCID: PMC10958389.
Learn More
If you’re curious about meta-analyses, these resources will support your team’s journey.
- How to Conduct Meta-Analysis: A Basic Tutorial: Basu’s tutorial provides a straightforward, step-by-step guide
- A Guide to Understanding Meta-analysis: A clear overview by Israel & Richter (Journal of Orthopaedic & Sports Physical Therapy) of the statistical techniques used in meta-analyses
- The 5 Min Meta-Analysis: Understanding How to Read and Interpret a Forest Plot: Chang et al. simplified guide to forest plots
- Systematic Reviews and Meta-Analyses: Meta-Analyses: This Texas Tech University Libraries guide Includes video tutorials and free tools
Final Thoughts on Meta-Analysis
Meta-analyses are powerful tools for evidence synthesis, providing stronger conclusions than single studies. However, they require careful execution to avoid biases and misleading results.
🔍 I’d love to hear your thoughts on meta-analysis! Start a conversation in the comments below.
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References
1. Gurevitch J, Koricheva J, Nakagawa S, Stewart G. Meta-analysis and the science of research synthesis. Nature. 2018 Mar 1;555(7695):175–82.
2. Quintana DS. From pre-registration to publication: a non-technical primer for conducting a meta-analysis to synthesize correlational data. Front Psychol. 2015;6:1549.
3. Deeks J, Higgins J, Altman DG, McKenzie JE, Veroniki A. Chapter 10: Analysing data and undertaking meta-analyses. In: Higgins J, Thomas J, Chandler J, Cumpston M, Li T, Page M, et al., editors. Cochrane Handbook for Systematic Reviews of Interventions [Internet]. 6.5. Cochrane; 2024 [cited 2025 Mar 28]. Available from: https://training.cochrane.org/handbook/current/chapter-10
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