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Efficacy/toxicity dose-finding using hierarchical modeling for multiple populations

Kristen M Cunanan1, Joseph S Koopmeiners1

  • 1Memorial Sloan Kettering Cancer Center, Department of Epidemiology and Biostatistics, 485 Lexington Avenue 2nd Floor, New York, NY 10017, United States.

Contemporary Clinical Trials
|June 25, 2018
PubMed

Insights

Hierarchical modeling in oncology trials improves optimal dose identification by simultaneously assessing toxicity and efficacy. This approach enhances patient safety and treatment effectiveness in early-phase drug development.

Area of Science:

  • Oncology
  • Biostatistics
  • Clinical Trial Design

Background:

  • Traditional Phase I oncology trials focus solely on toxicity for dose-finding.
  • Biologically targeted agents necessitate evaluating both efficacy and toxicity simultaneously.
  • Previous work demonstrated benefits of hierarchical modeling for multi-population dose escalation.

Purpose of the Study:

  • To extend hierarchical modeling for Phase I-II oncology trials.
  • To adapt a multi-population dose-finding algorithm for simultaneous efficacy-toxicity evaluation.
  • To investigate novel probability models for integrated dose-finding.

Main Methods:

  • Developed three hierarchical extensions to probability models for efficacy and toxicity.
  • Considered parametric and non-parametric bivariate models for binary outcomes.
  • Adapted a dose-finding algorithm for multiple populations and integrated outcomes.

Main Results:

  • Hierarchical modeling significantly increases the probability of identifying the optimal dose.
  • The average number of patients treated at the optimal dose is increased.
  • An under-parameterized hierarchical model demonstrated robust and desirable operating characteristics.

Conclusions:

  • Hierarchical modeling offers an improved approach for dose-finding in Phase I-II oncology trials.
  • Simultaneous evaluation of efficacy and toxicity is crucial for targeted agents.
  • The proposed methods, particularly the under-parameterized model, enhance clinical trial efficiency and patient outcomes.
Keywords:
Continual reassessment methodDose-findingMultiple populationsPhase I-II

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