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Related Experiment Videos

Dose-finding with two agents in Phase I oncology trials.

Peter F Thall1, Randall E Millikan, Peter Mueller

  • 1Department of Biostatistics, Box 447, University of Texas, M. D. Anderson Cancer Center, 1515 Holcombe Blvd., Houston, Texas 77030, USA. rex@mdanderson.org

Biometrics
|November 7, 2003
PubMed
Summary

This study introduces an adaptive Bayesian clinical trial design for combining two cytotoxic agents. The method efficiently identifies safe and effective dose combinations using prior toxicity data.

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Area of Science:

  • Clinical Trials
  • Biostatistics
  • Pharmacology

Background:

  • Phase I clinical trials are crucial for determining safe drug dosages.
  • Combining cytotoxic agents presents unique challenges in dose-finding due to complex toxicity interactions.
  • Existing designs may not optimally balance safety and efficacy when evaluating multiple agents simultaneously.

Purpose of the Study:

  • To propose a novel adaptive two-stage Bayesian design for Phase I trials involving two cytotoxic agents.
  • To establish a framework for identifying acceptable dose combinations of combined therapies.
  • To integrate prior knowledge of single-agent toxicities into the design for improved efficiency.

Main Methods:

  • A parametric model is employed to describe the probability of toxicity as a function of two doses.

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  • Informative priors for single-agent toxicity are elicited from physicians or historical data.
  • Vague priors are utilized for parameters governing two-agent interactions.
  • An adaptive two-stage Bayesian approach guides dose escalation and de-escalation.

    • Main Results:

    • The proposed design allows for the identification of one or more acceptable dose combinations.
    • The method leverages existing single-agent toxicity data to inform the trial design.
    • A simulation study demonstrates the design's performance and applicability.
    • The design was applied to a trial involving gemcitabine and cyclophosphamide.

    Conclusions:

    • The adaptive Bayesian design offers an efficient and statistically sound approach for Phase I trials of combined cytotoxic agents.
    • This method enhances the utilization of prior information, potentially reducing trial duration and patient exposure.
    • The design provides a flexible framework for navigating the complexities of combination drug therapy dose-finding.