Quantification of PFS effect for oncology drug approvals
View Presentation View Presentation
*Cong Chen, Merck & Co., Inc.  Linda Z Sun, Merck & Co., Inc. 

Keywords: Accelerated approval, Bayesian analysis, Surrogate endpoint

How to determine whether the outcome from a registration trial with PFS as the primary endpoint is reasonably likely to predict an OS benefit, a requirement for approvals? Since there is no guidance, regulatory agencies tend to look for a compelling PFS effect coupled with an OS effect in the right direction without specification of the effect sizes and significance levels. To address this issue, we propose a synthesized approach to explicitly address the implicit OS objective.

The proposed approach is applied to real examples in the metastatic breast cancer setting and hypothetical examples in other settings. The design based on our approach will have a greater sample size than a conventional PFS trial but smaller sample size than a onventional OS trial. It directly addresses the elusive OS question that a conventional PFS trial cannot, no matter how good a surrogate endpoint PFS is.