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Bayesian optimal interval designs for phase I clinical trials

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  • Suyu Liu
  • Ying Yuan

Abstract

type="main" xml:id="rssc12089-abs-0001"> In phase I trials, effectively treating patients and minimizing the chance of exposing them to subtherapeutic and overly toxic doses are clinicians' top priority. Motived by this practical consideration, we propose Bayesian optimal interval (BOIN) designs to find the maximum tolerated dose and to minimize the probability of inappropriate dose assignments for patients. We show, both theoretically and numerically, that the BOIN design not only has superior finite and large sample properties but also can be easily implemented in a simple way similar to the traditional ‘3+3’ design. Compared with the well-known continual reassessment method, the BOIN design yields comparable average performance to select the maximum tolerated dose but has a substantially lower risk of assigning patients to subtherapeutic and overly toxic doses. We apply the BOIN design to two cancer clinical trials.

Suggested Citation

  • Suyu Liu & Ying Yuan, 2015. "Bayesian optimal interval designs for phase I clinical trials," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 64(3), pages 507-523, April.
    • Handle: RePEc:bla:jorssc:v:64:y:2015:i:3:p:507-523
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    File URL: http://hdl.handle.net/10.1111/rssc.2015.64.issue-3
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    Cited by:

    1. Qingyang Liu & Junxian Geng & Frank Fleischer & Qiqi Deng, 2022. "Efficacy-Driven Dose Finding with Toxicity Control in Phase I Oncology Studies," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(3), pages 413-431, December.
    2. Deborah Plana & Geoffrey Fell & Brian M. Alexander & Adam C. Palmer & Peter K. Sorger, 2022. "Cancer patient survival can be parametrized to improve trial precision and reveal time-dependent therapeutic effects," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    3. M. Clertant & J. O’Quigley, 2017. "Semiparametric dose finding methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1487-1508, November.
    4. Tianjian Zhou & Wentian Guo & Yuan Ji, 2020. "PoD-TPI: Probability-of-Decision Toxicity Probability Interval Design to Accelerate Phase I Trials," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(2), pages 124-145, July.
    5. Yimei Li & Ying Yuan, 2020. "PA‐CRM: A continuous reassessment method for pediatric phase I oncology trials with concurrent adult trials," Biometrics, The International Biometric Society, vol. 76(4), pages 1364-1373, December.
    6. Chen Li & Haitao Pan, 2020. "A phase I dose-finding design with incorporation of historical information and adaptive shrinking boundaries," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-18, August.

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