Multi-stage adaptive enrichment trial design with subgroup estimation

ABSTRACT

We consider the problem of estimating 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 effect sizes and sample sizes, simpler methods for subgroup estimation worked better than more complex tree-based regression approaches. We propose a three-stage design with a weighted inverse normal combination test to test the hypothesis of no treatment effect across the three stages.

KEYWORDS:

• Adaptive enrichment
• predictive biomarker
• subgroup estimation

Additional information

Funding

Ivanova’s work was supported in part by the NIH grant P01 CA142538. Dr. Nguyen and Dr. Ivanova’s work was supported in part by the NIH grant U24 HL138998.