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Abstract:
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Sequential designs are widely used in clinical trials. In some cases, it is more natural to construct stopping rules based on time-to-event variables. However, Bayesian decision-theoretic methods for designing group sequential monitoring with time-to-event endpoints have not been described in the literature. In this study, we propose a simulation-based solution for a single-armed Phase IIB study to decide whether a new treatment is non-inferior or inferior, relative to a standard. Once the decision boundaries are obtained, we compute Bayesian and frequentist operating characteristics including Type I error, power, and expected run length; we further explore the optimal number of interim looks and the effect of sample size on operating characteristics.
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