  Immunotherapies have revolutionized cancer treatment. Unlike chemotherapies,
immune agents often take longer time to show benefit, and the complex and
unique mechanism of action of these agents renders the use of multiple
endpoints more appropriate in some trials. These new features of immunotherapy
make conventional phase II trial designs, which assume a single binary endpoint
that is quickly ascertainable, inefficient and dysfunctional. We propose a
flexible and efficient time-to-event Bayesian optimal phase II (TOP) design.
The TOP design is efficient in that it allows real-time "go/no-go" interim
decision making in the presence of late-onset responses by using all available
data, and maximizes the statistical power for detecting effective treatments.
TOP is flexible in the number of interim looks and capable of handling simple
and complicated endpoints under a unified framework. We conduct simulation
studies to evaluate the operating characteristics of the TOP design.Compared to
some existing designs, the TOP design shortens the trial duration and has
higher power to detect effective treatment with well controlled type I errors.
The TOP design allows for making real-time "go/no-go" interim decisions in the
presence of late-onset responses, and is capable of handling various types of
endpoints under a unified framework. It is transparent and easy to implement as
its decision rules can be tabulated and included in the protocol prior to the
conduct of the trial. The TOP design provides a flexible, efficient and
easy-to-implement method to accelerate and improve the development of
immunotherapies.
