Affiliation:
1. Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX
2. Department of Gynecologic Oncology and Reproductive Medicine, University of Texas MD Anderson Cancer Center, Houston, TX
Abstract
Abstract
Background
Immunotherapies have revolutionized cancer treatment. Unlike chemotherapies, immune agents often take longer 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.
Methods
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 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.
Results
In the considered trial settings, compared to some existing Bayesian designs, the TOP design shortens the trial duration by 4–10 months and improves the power to detect effective treatment up to 90%, with well-controlled type I errors.
Conclusions
The TOP design 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.
Funder
National Institutes of Health
Cancer Prevention Research Institute of Texas
Ovarian Cancer Research Fund
Ann Rife Cox Chair in Gynecology
Publisher
Oxford University Press (OUP)
Cited by
12 articles.
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