Analysis and interpretations of findings from subgroup comparisons: within randomized controlled clinical trials,Used

Analysis and interpretations of findings from subgroup comparisons: within randomized controlled clinical trials,Used

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This thesis explores subgroup analyses within randomized trials,using cardiovascular interventions as a focal point.Reviewing 67 large trialspublished between 1980 and 1997,we found that most reported on multiple singlefactor subgroups without prespecification or stastical tests for subgrouptreatment interactions.Instead of singlefactor subgroups without prespecification or stastical tests for subgroup treatment interactions.Instead of singlefactor subgroup analyses,decisionmakers can infer absolute benefits by appplying the relative effect size from the overall trial to baseline event rates in subgroups.We tested this approach in the SOLVD prevention (4228patients) and treatment(2569 patients)trials.We confirmed a published treatment interaction with ejection fraction(p=0.004),but successfully abolished that interaction when patients were divided into multivariate tertiles of baseline prognostic risk.This lack of significant variation could represent a beta error.We found no published method to perform a posthoc power test for the most popular interaction test,the BreslowDay statistic.

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