Bayesian Power-Based Sample Size Determination for Single-Arm Clinical Trials With Time-to-Event Endpoints

The purpose of an exploratory clinical trial is to determine whether a new treatment is worth evaluating in subsequent trials. These trials often assessed the efficacy and safety of a single-arm design with binary outcomes. In cancer therapy, time-to-event may be the primary endpoint. In such cases, the frequentist method is typically used to determine sample size. The Bayesian method has recently attracted attention from the perspective of using prior information and introducing early termination criteria. We propose a sample size determination method based on Bayesian power using the posterior probability and prior predictive probability of the hazard ratio (parameter), assuming that the survival functions of historical control and new treatment have proportional hazards. The prior information of the parameter is expressed as the analysis prior and the uncertainty of the parameter is expressed as the design prior. To conduct the clinical trial efficiently, we extended the study design to include early termination criteria. The simulation results showed that the sample size decreased when using an informative analysis prior, whereas it increased when using a design prior that accounted for variance, thus allowing for a more conservative sample size design while taking advantage of the available prior information.