Subgroup analysis in randomised controlled trials: importance, indications, and interpretation
Abstract
Large pragmatic trials provide the most reliable data about the effects of treatments, but should be designed, analysed, and reported to enable the most effective use of treatments in routine practice. Subgroup analyses are important if there are potentially large differences between groups in the risk of a poor outcome with or without treatment, if there is potential heterogeneity of treatment effect in relation to pathophysiology, if there are practical questions about when to treat, or if there are doubts about benefit in specific groups, such as elderly people, which are leading to potentially inappropriate undertreatment. Analyses must be predefined, carefully justified, and limited to a few clinically important questions, and post-hoc observations should be treated with scepticism irrespective of their statistical significance. If important subgroup effects are anticipated, trials should either be powered to detect them reliably or pooled analyses of several trials should be undertaken. Formal rules for the planning, analysis, and reporting of subgroup analyses are proposed.
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In RCTs, interaction analysis, if incorrectly tested or misinterpreted, may lead to unnecessary withholding of treatment, ineffective or even harmful treatment effects.
“Although interaction analysis in RCTs is usually stated as the secondary study objective, if incorrectly tested or misinterpreted, it may lead to unnecessary withholding of treatment, ineffective or even harmful treatment effects.”
From Understanding of interaction (subgroup) analysis in clinical trials (2019) · cites this paper as [2]
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- Authors
- Rothwell, P. M.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Rothwell, Peter M
- ORCID
- Rothwell, Peter M
- Venue
- The Lancet
- Publisher
- Elsevier BV
- Published
- 2005-01
- Volume
- 365
- Issue
- 9454
- Pages
- 176-186
- ISSN
- 0099-5355 (ISSN-L)
- 0140-6736
- OpenAlex
- W2148173212
- Cited by
- 942
- References
- 134
- Citations by year
- 2026: 35 · 2025: 56 · 2024: 45 · 2023: 34 · 2022: 42 · 2021: 50 · 2020: 53 · 2019: 47 · 2018: 33 · 2017: 65 · 2016: 66 · 2015: 56 · 2014: 42 · 2013: 40 · 2012: 50
- FWCI
- 35.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Lancet (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Keywords
- subgroup analysis, randomized controlled trials, treatment effect heterogeneity, pragmatic trials, trial design, post hoc analysis, treatment timing, trial power, meta-analysis
- MeSH terms
- Data Interpretation, Statistical, Humans, Research Design, Randomized Controlled Trials as Topic, Treatment Outcome
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