All Times EDT
Keywords: Subgroup estimation in an enrichment trial with multiple biomarkers
We consider the problem of estimating or identifying the best subgroup and testing for treatment effect in a clinical trial. We define the best subgroup as the subgroup that maximizes a utility function that reflects the trade-off between the subgroup size and the treatment effect. For moderate effects sizes and sample sizes, simpler methods for subgroup estimation worked better than more complex tree- based regression approaches. We propose a three-stage design, where the subgroup is estimated at the first interim analysis and then refined in the second interim analysis. A weighted inverse normal combination test is used to test the hypothesis of no treatment effect across the three stages.