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Effective sample size for computing prior hyperparameters in Bayesian phase I-II dose-finding.

Peter F Thall1, Richard C Herrick2, Hoang Q Nguyen2

  • 1Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA rex@mdanderson.org.

Clinical Trials (London, England)
|September 3, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces improved methods for Bayesian phase I-II dose-finding, enhancing the efficacy-toxicity trade-off design. New guidelines and algorithms ensure more reliable prior hyperparameters and contour specifications for better clinical trial outcomes.

Keywords:
Adaptive designBayesian designclinical trialdose-findingphase I/II trial

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Pharmacometrics

Background:

  • The efficacy-toxicity trade-off design is a practical Bayesian method for phase I-II dose-finding.
  • Proper specification of prior hyperparameters and the target trade-off contour is crucial for design performance.

Purpose of the Study:

  • To develop a method for deriving priors from elicited mean outcome probabilities, balancing informativeness and dispersion.
  • To provide practical guidelines for specifying the target trade-off contour in dose-finding studies.

Main Methods:

  • A general algorithm using penalized least squares with effective sample size to determine prior hyperparameters.
  • Development of guidelines for specifying the trade-off contour.
  • Illustration with a clinical trial in advanced prostate cancer and provision of an updated software program.

Main Results:

  • The proposed algorithm and guidelines significantly improve the operating characteristics of the efficacy-toxicity design.
  • Substantive enhancements in practical usefulness and ease of implementation through an updated computer program.

Conclusions:

  • The method requires substantial elicited values and design parameters, necessitating computer simulations for optimal design.
  • The general algorithm for prior hyperparameter determination can be applied beyond the efficacy-toxicity method, enhancing its broad applicability.