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In oncology, phase II studies are crucial for clinical development plans assuch studies identify potent agents with sufficient activity to continuedevelopment in the subsequent phase III trials. Traditionally, phase II studiesare single-arm studies, with the primary endpoint being short-term treatmentefficacy. However, drug safety is also an important consideration. In thecontext of such multiple-outcome designs, predictive probability-based Bayesianmonitoring strategies have been developed to assess whether a clinical trialwill provide enough evidence to continue with a phase III study at thescheduled end of the trial. Herein, we propose a new simple index vector forsummarizing results that cannot be captured by existing strategies.Specifically, for each interim monitoring time point, we calculate the Bayesianpredictive probability using our new index and use it to assign a go/no-godecision. Finally, simulation studies are performed to evaluate the operatingcharacteristics of the design. The obtained results demonstrate that theproposed method makes appropriate interim go/no-go decisions.

Bayesian predictive probability based on a bivariate index vector for single-arm phase II study with binary efficacy and safety endpoints