Analysis of clinical trial outcomes: some comments on subgroup analyses.
This article briefly discusses the various ways in which prognostic information can be included in the analysis of treatment effect in clinical trials. Adjustments in the treatment comparison are usually not warranted, as they do not substantially improve precision, but they may be useful, in addition to the unadjusted comparison, if a potent covariate is by chance maldistributed among the treatment groups. Estimation of interactions between treatment and covariates is usually plagued by insufficient statistical power. Estimation of treatment effect within individual subgroups is also subject to large random errors as well as to the problem of multiplicity, but with these caveats in mind it is an informative and needed complement to an analysis of overall treatment effect.
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European Organization for Research and Treatment of Cancer, Data Center, Brussels, Belgium.
D016000:Cluster Analysis; D015986:Confounding Factors, Epidemiologic; D006801:Humans; D011379:Prognosis; D016016:Proportional Hazards Models; D016032:Randomized Controlled Trials as Topic / Q000592:standards*; D012307:Risk Factors