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An optimization algorithm for designing phase I cancer clinical trials

Abstract Numerous phase I dose finding clinical trials are conducted everyday to find the “maximum tolerated dose” (MTD) of a cancer treatment. Although various Bayesian designs for Phase I clinical trials have been proposed in the literature, the traditional 3 + 3 design is still widely used becaus...

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Bibliographic Details
Published in:Contemporary clinical trials 2008-03, Vol.29 (2), p.102-108
Main Authors: Jiang, Hui, Liu, Yifan, Su, Zheng
Format: Article
Language:English
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Summary:Abstract Numerous phase I dose finding clinical trials are conducted everyday to find the “maximum tolerated dose” (MTD) of a cancer treatment. Although various Bayesian designs for Phase I clinical trials have been proposed in the literature, the traditional 3 + 3 design is still widely used because of its algorithm-based simplicity in logistics for the clinical investigators to carry out in comparison with model-based Bayesian methods. In this paper, we propose an optimization algorithm for designing phase I cancer clinical trials. This algorithm does not need assumptions on the true dose-response relationship but can readily incorporate available prior information about the true response probabilities. It searches for an approximately optimal design within a design space, in which the 3 + 3 design is included as a special case. Simulation studies show that the design recommended by this algorithm significantly outperforms the 3 + 3 design.
ISSN:1551-7144
1559-2030
DOI:10.1016/j.cct.2007.06.003