Network meta-analysis: an introduction for clinicians
Open accessAbstract
Network meta-analysis is a technique for comparing multiple treatments simultaneously in a single analysis by combining direct and indirect evidence within a network of randomized controlled trials. Network meta-analysis may assist assessing the comparative effectiveness of different treatments regularly used in clinical practice and, therefore, has become attractive among clinicians. However, if proper caution is not taken in conducting and interpreting network meta-analysis, inferences might be biased. The aim of this paper is to illustrate the process of network meta-analysis with the aid of a working example on first-line medical treatment for primary open-angle glaucoma. We discuss the key assumption of network meta-analysis, as well as the unique considerations for developing appropriate research questions, conducting the literature search, abstracting data, performing qualitative and quantitative synthesis, presenting results, drawing conclusions, and reporting the findings in a network meta-analysis.
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A random effects model was employed to calculate the results.
“The assumption of common heterogeneity between studies is unreliable when involve each comparison in numerous studies, so we employed a random effects model to calculate the results.[24]”
From Effectiveness of visible light for seasonal affective disorder: A systematic review and network meta-analysis (2025) · cites this paper as [24]
The Quantitative synthesis section says comparison-specific heterogeneity may be preferred when many studies inform each comparison and common heterogeneity is not plausible. It does not say that this calls for a random-effects model or document the citing authors’ use of one to calculate their results. (LLM, conf=0.84)
Experimental — accuracy not yet measuredNetwork meta-analysis is a powerful tool that compares multiple treatments simultaneously in a single systematic evaluation, providing better clinical decisions.
“Therefore, NMA is believed as a powerful tool to compare the effectiveness of multiple studies.[23]”
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- Authors
- Rouse, B., Chaimani, A., & Li, T.
- Affiliations
- Johns Hopkins University (US)
- University of Ioannina (GR)
- Corresponding author
- Li, Tianjing
- Venue
- Internal and Emergency Medicine
- Published
- 2016-12-02
- Volume
- 12
- Issue
- 1
- Pages
- 103-111
- ISSN
- 1828-0447 (ISSN-L)
- 1970-9366
- PMC
- PMC5247317
- OpenAlex
- W2558697804
- Cited by
- 875
- References
- 42
- Citations by year
- 2026: 105 · 2025: 158 · 2024: 166 · 2023: 155 · 2022: 128 · 2021: 82 · 2020: 48 · 2019: 21 · 2018: 10 · 2017: 2
- FWCI
- 10.27
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Internal and Emergency Medicine (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Eye Institute (U01EY020522, RC1EY020140)
- 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, primary open-angle glaucoma, comparative effectiveness, randomized controlled trials, circumstantial evidence, research question formulation, data abstraction, reporting guidelines
- MeSH terms
- Network Meta-Analysis as Topic, Humans, Research, Research Design, Review Literature as Topic, Models, Statistical
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