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