Investigation of Trial characteristics and Optimal Alpha Split in Correlated Dual Primary Endpoint

Music City Center 

Progression-free survival (PFS) and overall survival (OS) are often used as dual primary endpoints in Phase 3 oncology trials. However, current sample size calculation tools struggle to account for correlation between these endpoints, leading to adoption of a conservative approach assuming their independence. Further, subjective and arbitrary decision on the alpha split between the dual primary endpoints may not be optimal given extent of correlation and additional trial design features. We propose a simulation framework for this setting, inducing correlation using the Copula method and the Moran Downtown model. This will be tested across scenarios with different sample sizes, alpha splits, and correlation levels. Our goal is to assess trial characteristics like power and type I error, providing a framework for generating correlated PFS and OS endpoints. By simulating correlated endpoints, we aim to offer a more accurate representation of their relationship, leading to better-informed trial designs with more precise sample size. This approach will help optimize alpha allocation to maintain desired power, ultimately enhancing the design, analysis and duration of oncology trials.

Oncology

Clinical Trials

Progression Free Survival

Overall Survival

Dual primary endpoints 

Biopharmaceutical Section