Statistics in Medicine — Reporting of Subgroup Analyses in Clinical Trials

Wang, Rui; Lagakos, Stephen W.; Ware, James H.; Hunter, David J.; Drazen, Jeffrey M.

doi:10.1056/nejmsr077003

Cited by 1,445Statistical Methods in Clinical TrialsMeta-analysis and systematic reviewsStatistical Methods in Epidemiology

Statistics in Medicine — Reporting of Subgroup Analyses in Clinical Trials

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Wang, Rui, Lagakos, Stephen W., Ware, James H., Hunter, David J., Drazen, Jeffrey M.·2007·New England Journal of Medicine

DOI 10.1056/nejmsr077003

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Abstract

The analysis of subgroups is often used as a way to glean additional information from data sets. The strengths and weaknesses of this approach and new Journal policies concerning the reporting of subgroup analyses are discussed in this article.

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In 68% of the studies testing interaction, it was unclear whether analyses were prespecified or post hoc.
“In 2007, Wang et al 1 evaluated 97 RCTs of which 61% tested interactions, but in 68% of the studies testing interaction, it was unclear whether analyses were prespecified”
From Understanding of interaction (subgroup) analysis in clinical trials (2019) · cites this paper as [1]
In 2007, Wang et al evaluated 97 RCTs, of which 61% tested interactions.
“In 2007, Wang et al 1 evaluated 97 RCTs of which 61% tested interactions, but in 68% of the studies testing interaction, it was unclear whether analyses were prespecified”
From Understanding of interaction (subgroup) analysis in clinical trials (2019) · cites this paper as [1]
Only 27% of the studies testing interaction reported formal testing.
“or post hoc and only 27% of them reported formal testing.”
From Understanding of interaction (subgroup) analysis in clinical trials (2019) · cites this paper as [1]
The constant effect assumption makes the average causal effect relevant to each patient.
“Following Holland 13, this assumption has the advantage of making the average causal effect relevant to each patient.”
From Does evidence support the high expectations placed in precision medicine? A bibliographic review (2019) · cites this paper as [13]

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Authors: Wang, R., Lagakos, S. W., Ware, J. H., Hunter, D. J., & Drazen, J. M.
ORCID: Wang, Rui
Drazen, Jeffrey M.
Venue: New England Journal of Medicine
Publisher: Massachusetts Medical Society
Published: 2007-11-22
Volume: 357
Issue: 21
Pages: 2189-2194
ISSN: 0028-4793 (ISSN-L)
1533-4406
DOI: 10.1056/nejmsr077003
OpenAlex: W2098931866
Cited by: 1,445
References: 22
Citations by year: 2026: 82 · 2025: 71 · 2024: 85 · 2023: 62 · 2022: 77 · 2021: 84 · 2020: 115 · 2019: 98 · 2018: 74 · 2017: 76 · 2016: 70 · 2015: 72 · 2014: 70 · 2013: 66 · 2012: 73
FWCI: 62.89
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: New England Journal of Medicine (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 › Statistical Methods in Epidemiology
Keywords: subgroup analysis, clinical trials, statistical reporting, journal editorial policy, publication bias, treatment effect heterogeneity
MeSH terms: Clinical Trials as Topic, Data Interpretation, Statistical, Quality Control, Statistics as Topic

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Statistics in Medicine — Reporting of Subgroup Analyses in Clinical Trials

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