Robin Vernooij, Post-doctoral researcher at University Medical Center UtrechtSubgroup analyses are a useful tool to investigate the possibility of differing treatment effects between subgroups of patients with certain characteristics (e.g., women vs men, old vs young, more versus less severe disease status). Nevertheless, its methodology and reporting are not always adequately used. Hence, criteria for assessing the credibility of subgroup analyses, nicely summarized in a formal Instrument for Assessing the Credibility of Effect Modification Analyses (ICEMAN), include investigator postulation of a priori hypotheses with a specified direction; support from prior evidence; a low likelihood that chance explains the apparent subgroup effect; and only testing a small number of subgroup hypotheses. In this mini-review, we explore the common pitfalls of subgroup analyses.
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