Sample size and power considerations in network meta-analysis
Open accessAbstract
BACKGROUND: Network meta-analysis is becoming increasingly popular for establishing comparative effectiveness among multiple interventions for the same disease. Network meta-analysis inherits all methodological challenges of standard pairwise meta-analysis, but with increased complexity due to the multitude of intervention comparisons. One issue that is now widely recognized in pairwise meta-analysis is the issue of sample size and statistical power. This issue, however, has so far only received little attention in network meta-analysis. To date, no approaches have been proposed for evaluating the adequacy of the sample size, and thus power, in a treatment network. FINDINGS: In this article, we develop easy-to-use flexible methods for estimating the 'effective sample size' in indirect comparison meta-analysis and network meta-analysis. The effective sample size for a particular treatment comparison can be interpreted as the number of patients in a pairwise meta-analysis that would provide the same degree and strength of evidence as that which is provided in the indirect comparison or network meta-analysis. We further develop methods for retrospectively estimating the statistical power for each comparison in a network meta-analysis. We illustrate the performance of the proposed methods for estimating effective sample size and statistical power using data from a network meta-analysis on interventions for smoking cessation including over 100 trials. CONCLUSION: The proposed methods are easy to use and will be of high value to regulatory agencies and decision makers who must assess the strength of the evidence supporting comparative effectiveness estimates.
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Network meta-analysis can improve precision of estimates by integrating direct and indirect treatment effect estimates.
“Furthermore, since NMA can improve the precision of estimates by allowing integration of both direct and indirect treatment effect estimates 26 , it is recommended over pairwise meta-analyses by the World Health Organization as a basis for clinical guidelines 27 .”
From Lack of evidence to favor specific preventive interventions in psychosis: a network meta‐analysis (2018) · cites this paper as [26]
Combining indirect with direct evidence through network meta-analysis increases the power and precision of treatment effect estimates relative to pairwise analyses.
“In the context of power considerations, indirect evidence, when combined with direct evidence through NMA, increases the power and precision of treatment effect estimates compared to pairwise analyses 26 .”
From Lack of evidence to favor specific preventive interventions in psychosis: a network meta‐analysis (2018) · cites this paper as [26]
Capitalizing on the increased power and precision of network meta-analysis, the Cochrane group has conducted such analyses in even smaller databases, including as few as three to seven studies.
“However, capitalizing on the increased power and precision of NMA 26 , the Cochrane group has conducted such analysis in even smaller databases, including as few as three to seven studies [110][111][112][113] .”
From Lack of evidence to favor specific preventive interventions in psychosis: a network meta‐analysis (2018) · cites this paper as [26]
The study included only RCTs with total sample size >20 to reduce risk of publication bias.
“with a total sample size of more than 20 participants to reduce the risk of publication bias”
From Comparative Effectiveness of Multiple Exercise Interventions in the Treatment of Mental Health Disorders: A Systematic Review and Network Meta-Analysis (2022) · cites this paper as [28]
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References 39 · Cited by 197
- Authors
- Thorlund, K., & Mills, E. J.
- Affiliations
- McMaster University (CA)
- Corresponding author
- Thorlund, Kristian
- Venue
- Systematic Reviews
- Published
- 2012-09-19
- Volume
- 1
- Issue
- 1
- Pages
- 41-41
- ISSN
- 2046-4053 (ISSN-L)
- PMC
- PMC3514119
- OpenAlex
- W2142056543
- Cited by
- 197
- References
- 39
- Citations by year
- 2026: 13 · 2025: 20 · 2024: 15 · 2023: 8 · 2022: 17 · 2021: 19 · 2020: 13 · 2019: 11 · 2018: 19 · 2017: 15 · 2016: 7 · 2015: 21 · 2014: 12 · 2013: 7
- FWCI
- 14.55
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Systematic Reviews (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Social Sciences › Sociology and Political Science › Delphi Technique in Research
- Keywords
- network meta-analysis, sample size, statistical power, effective sample size, indirect comparison, quality of evidence, smoking cessation interventions, comparative effectiveness
- MeSH terms
- Clinical Trials as Topic, Humans, Research Design, Meta-Analysis as Topic, Models, Statistical, Sample Size, Evidence-Based Medicine, Comparative Effectiveness Research
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