Outcome based subgroup analysis: a neglected concern
Open accessAbstract
BACKGROUND: A subgroup of clinical trial subjects identified by baseline characteristics is a proper subgroup while a subgroup determined by post randomization events or measures is an improper subgroup. Both types of subgroups are often analyzed in clinical trial papers. Yet, the extensive scrutiny of subgroup analyses has almost exclusively attended to the former. The analysis of improper subgroups thereby not only flourishes in numerous disguised ways but also does so without a corresponding awareness of its pitfalls. Comparisons of the grade of angina in a heart disease trial, for example, usually include only the survivors. This paper highlights some of the distinct ways in which outcome based subgroup analysis occurs, describes the hazards associated with it, and proposes a simple alternative approach to counter its analytic bias. RESULTS: Data from six published trials show that outcome based subgroup analysis, like proper subgroup analysis, may be performed in a post-hoc fashion, overdone, selectively reported, and over interpreted. Six hypothetical trial scenarios illustrate the forms of hidden bias related to it. That bias can, however, be addressed by assigning clinically appropriate scores to the usually excluded subjects and performing an analysis that includes all the randomized subjects. CONCLUSION: A greater level of awareness about the practice and pitfalls of outcome based subgroup analysis is needed. When required, such an analysis should maintain the integrity of randomization. This issue needs greater practical and methodologic attention than has been accorded to it thus far.
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Defining subgroups based on variables measured after randomisation is susceptible to bias.
“Defining subgroups based on variables measured after randomisation is susceptible to bias and should be avoided.442”
From SPIRIT 2025 explanation and elaboration: updated guideline for protocols of randomised trials (2025) · cites this paper as [442]
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- Authors
- Hirji, K. F., & Fagerland, M. W.
- Affiliations
- Muhimbili University of Health and Allied Sciences (TZ)
- Oslo University Hospital (NO)
- Corresponding author
- Fagerland, Morten W
- ORCID
- Fagerland, Morten W
- Venue
- Trials
- Published
- 2009-05-20
- Volume
- 10
- Issue
- 1
- Pages
- 33-33
- ISSN
- 1745-6215 (ISSN-L)
- PMC
- PMC2693510
- OpenAlex
- W2156597715
- Cited by
- 41
- References
- 33
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 1 · 2023: 3 · 2022: 2 · 2021: 5 · 2020: 8 · 2019: 2 · 2018: 3 · 2017: 3 · 2016: 2 · 2014: 2 · 2013: 2 · 2012: 2
- FWCI
- 1.38
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Trials (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- IHI Repository (acceptedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
- 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
- proper subgroups, hidden bias, post hoc analysis, selective reporting, survivorship bias, clinical trial design
- MeSH terms
- Clinical Trials as Topic, Data Interpretation, Statistical, Humans, Research Design, Reproducibility of Results, Bias, Survival Analysis, Treatment Outcome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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