TOP: Time-to-Event Bayesian Optimal Phase II Trial Design for Cancer Immunotherapy

Clicks: 94
ID: 281566
2018
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Abstract
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.
Reference Key
yuan2018top Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ruitao Lin; Robert L Coleman; Ying Yuan
Journal arXiv
Year 2018
DOI
DOI not found
URL
http://arxiv.org/abs/1810.00709v1
Keywords
stat.ap stat.me

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