1. [How to interpret subgroup analyses in cardiovascular trials?]
- Author
-
Basile C and Maggioni AP
- Subjects
- Humans, Randomized Controlled Trials as Topic, Data Interpretation, Statistical, Research Design, Clinical Trials as Topic, Cardiovascular Diseases
- Abstract
Clinical trials provide the best evidence on the effect of a treatment, but they evaluate this effect on the total population of the study as if the effect of the randomized treatment was identical in all possible subgroups of patients (young, elderly, male, female, etc.). Subgroup analyses are an important tool to evaluate the presence of any diversity of the treatment effect concerning specific patient characteristics, if there are practical questions about who to treat and when, or if there are doubts about the benefit/risk profile of a therapy in a specific subpopulation. Subgroup analyses should be defined a priori, biologically plausible, and limited to few clinically important questions. Subgroup analyses have greater relevance in the context of studies that have demonstrated an overall significant difference between treatments. In the case of neutral or negative studies, any significant analyses between subgroups should be considered as essentially exploratory. Post-hoc subgroup analyses should be treated with great caution and considered more credible as the results are consistent with other studies. If significant heterogeneity is expected in specific subgroups of patients when planning a trial, they should have sufficient statistical power to detect the difference in the effect. In this review, we propose a critical approach for interpreting subgroup analyses in cardiovascular trials.
- Published
- 2024
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