Bayesian trial design to identify a sensitive subpopulation in non-proportional hazard settings

Music City Center 

In molecular targeted therapy drug development, biomarkers are often incorporated into clinical trial designs. Recently, there has been much discussion on the challenges and advantages of this approach. Identifying subpopulations of patients who benefit from new treatments based on biomarker expression can facilitate smoother drug development.
Morita et al. (2014) proposed a Bayesian phase II trial design to identify subpopulations with high treatment efficacy based on biomarker expression. To reduce the required sample size, the design was later extended to allow stepwise determination of treatment effectiveness or ineffectiveness for each subpopulation (Sugitani et al., 2023). However, both approaches use the hazard ratio as the primary endpoint and are not applicable when the proportional hazards assumption does not hold.
To address this limitation, we extend Morita et al.'s Bayesian clinical trial design by incorporating the restricted mean survival time (RMST) as the primary endpoint. Since RMST does not require the proportional hazards assumption, our proposed approach extends the applicability of biomarker-based Bayesian phase II clinical trials.

Bayesian clinical trial design

Phase II trial

Subpopulation identification

Restricted mean survival time

Survival analysis 

Biopharmaceutical Section