Adaptive group sequential design for phase II clinical trials: A Bayesian decision theoretic approach

Bayesian decision theoretic approaches (BDTAs) have been widely studied in the literature as tools for designing and conducting phase II clinical trials. However, full Bayesian approaches that consider multiple endpoints are lacking. Since the monitoring of toxicity is a major goal of phase II trials, we propose an adaptive group sequential design using a BDTA, which characterizes efficacy and toxicity as correlated bivariate binary endpoints. We allow trade-off between the two endpoints. Interim evaluations are conducted group sequentially, but the number of interim looks and the size of each group are chosen adaptively based on current observations. We utilize a loss function consisting of two components: the loss associated with accruing, treating, and monitoring patients, and the loss associated with making incorrect decisions. The performance of our Bayesian modeling, and the operating characteristics of decision rules under a wide range of loss function parameters are evaluated using seven scenarios in a simulation study. Our method is illustrated in the context of a single-arm phase II trial of bevacizumab, gemcitabine, and oxaliplatin in patients with metastatic pancreatic adenocarcinoma.