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Adaptive Bayesian phase I clinical trial designs for estimating the maximum tolerated doses for two drugs while fully utilizing all toxicity information

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Last modified
  • 09/19/2025
Type of Material
Authors
    Yuzi Zhang, Emory UniversityMichael Kutner, Emory UniversityZhengjia Chen, Emory University
Language
  • English
Date
  • 2021-05-10
Publisher
  • WILEY
Publication Version
Copyright Statement
  • © 2021 Wiley-VCH GmbH
Final Published Version (URL)
Title of Journal or Parent Work
Volume
  • 63
Issue
  • 7
Start Page
  • 1476
End Page
  • 1492
Supplemental Material (URL)
Abstract
  • The combined treatments with multiple drugs are very common in the contemporary medicine, especially for medical oncology. Therefore, we developed a Bayesian adaptive Phase I clinical trial design entitled escalation with overdoing control using normalized equivalent toxicity score for estimating maximum tolerated dose (MTD) contour of two drug combination (EWOC-NETS-COM) used for oncology trials. The normalized equivalent toxicity score (NETS) as the primary endpoint of clinical trial is assumed to follow quasi-Bernoulli distribution and treated as quasi-continuous random variable in the logistic linear regression model which is used to describe the relationship between the doses of the two agents and the toxicity response. Four parameters in the dose–toxicity model were re-parameterized to parameters with explicit clinical meanings to describe the association between NETS and doses of two agents. Noninformative priors were used and Markov chain Monte Carlo was employed to update the posteriors of the four parameters in dose–toxicity model. Extensive simulations were conducted to evaluate the safety, trial efficiency, and MTD estimation accuracy of EWOC-NETS-COM under different scenarios, using the EWOC as reference. The results demonstrated that EWOC-NETS-COM not only efficiently estimates MTD contour of multiple drugs but also provides better trial efficiency by fully utilizing all toxicity information.
Author Notes
  • Dr. Zhengjia Chen, Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, 1603 West Taylor Street, SPHPI 947, Chicago, IL 60612, USA. Email: znchen@uic.edu
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