Design Considerations in Clinical Trials with Cure Rate Survival Data: a Case Study in Oncology

• Activity Number: 307 - Clinical Trial Design-3
• Type: Contributed
• Date/Time: Tuesday, July 31, 2018 : 8:30 AM to 10:20 AM
• Sponsor: Biopharmaceutical Section
• Author(s): Grace Liu* and Steven Sun and Tzu-min Yhe and Tianmeng Lyu and Rao Sudhakar and Bruce Xue
• Companies: Johnson & Johnson and J&J and janssen pharmaceuticals and University of Minnesota and janssen pharmaceuticals and Johnson & Johnson China
• Keywords: cure rate survival data; log-rank test; survival analysis; clinical trial design; weighted KM test; restricted mean survival time (RMST)

Abstract

For clinical trials with time to event as the primary endpoint, the clinical cutoff is often event driven and the log-rank test is the most commonly used statistical method for evaluating treatment effect. However, this method relies on the proportional hazards assumption in that it has the maximal power in this circumstance. In certain disease areas or populations, some patients can be curable and never experience the events despite a long follow?up. The event accumulation may dry out after a certain period of follow?up and the treatment effect could be reflected as the combination of improvement of cure rate and the delay of events for those uncurable patients. Study power depends on both cure rate improvement and hazard reduction. In this paper, we illustrate these practical issues using simulation studies and explore sample size recommendations, alternative ways for clinical cutoffs, and efficient testing methods with the highest study power possible.