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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

Supported in part by NIH/NCI grant nos. 1 P01 CA116676 (ZC and MK), 1 P50 CA217691–01A1 (ZC and MK). We thank Dr. Anthea Hammond for editing. Research reported in this publication was supported in part by the University of Illinois Cancer Center Biostatistics Shared Resource (BSR) core (ZC). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

The author(s) declared no potential conflict of interest with respect to the research, authorship, and/or publication of this article.

Subjects:

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Physical Sciences
  • Mathematical & Computational Biology
  • Statistics & Probability
  • Mathematics
  • cancer phase I clinical trial
  • drug combination
  • escalation with overdose control
  • maximum tolerated dose curve
  • quasi&#8208
  • continuous toxicity response
  • INTERVAL DESIGN
  • COMBINATIONS
  • ESCALATION
  • ONCOLOGY
  • AGENTS
  • BURDEN
  • SCORE

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

Tools:

Journal Title:

BIOMETRICAL JOURNAL

Volume:

Volume 63, Number 7

Publisher:

, Pages 1476-1492

Type of Work:

Article | Post-print: After Peer Review

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.
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