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• W4364353507 abstract "Abstract Designs for early phase dose finding clinical trials typically are either phase I based on toxicity, or phase I‐II based on toxicity and efficacy. These designs rely on the implicit assumption that the dose of an experimental agent chosen using these short‐term outcomes will maximize the agent's long‐term therapeutic success rate. In many clinical settings, this assumption is not true. A dose selected in an early phase oncology trial may give suboptimal progression‐free survival or overall survival time, often due to a high rate of relapse following response. To address this problem, a new family of Bayesian generalized phase I‐II designs is proposed. First, a conventional phase I‐II design based on short‐term outcomes is used to identify a set of candidate doses, rather than selecting one dose. Additional patients then are randomized among the candidates, patients are followed for a predefined longer time period, and a final dose is selected to maximize the long‐term therapeutic success rate, defined in terms of duration of response. Dose‐specific sample sizes in the randomization are determined adaptively to obtain a desired level of selection reliability. The design was motivated by a phase I‐II trial to find an optimal dose of natural killer cells as targeted immunotherapy for recurrent or treatment‐resistant B‐cell hematologic malignancies. A simulation study shows that, under a range of scenarios in the context of this trial, the proposed design has much better performance than two conventional phase I‐II designs." @default.
• W4364353507 created "2023-04-12" @default.
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• W4364353507 date "2023-04-11" @default.
• W4364353507 modified "2023-10-17" @default.
• W4364353507 title "Generalized phase <scp>I‐II</scp> designs to increase long term therapeutic success rate" @default.
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• W4364353507 doi "https://doi.org/10.1002/pst.2301" @default.
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