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Evaluating multiple treatment courses in clinical trials.

P F Thall1, R E Millikan, H G Sung

  • 1Department of Biostatistics, The University of Texas, M.D. Anderson Cancer Center, Houston 77030, USA.

Statistics in Medicine
|May 3, 2000
PubMed
Summary
This summary is machine-generated.

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This study introduces a new statistical framework for multi-course cancer chemotherapy trials. It enhances patient information by reflecting adaptive treatment strategies used in clinical practice.

Area of Science:

  • Oncology
  • Biostatistics
  • Clinical Trial Design

Background:

  • Cancer treatment often involves sequential chemotherapy courses.
  • Current statistical methods often oversimplify patient outcomes in multi-course treatments.
  • Adaptive treatment strategies like 'play-the-winner' are common but not fully captured by traditional analyses.

Purpose of the Study:

  • To develop a statistical framework for multi-course clinical trials that mirrors adaptive treatment selection.
  • To maximize information gained per patient in oncology trials.
  • To better align trial design with actual clinical practice.

Main Methods:

  • Proposed a design similar to multi-stage cross-over trials with adaptive treatment assignment after the first course.
  • Applied the framework to a randomized phase II trial for androgen independent prostate cancer.

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  • Considered objectives for selecting the single best treatment or a best ordered pair of treatments.

    • Main Results:

    • The framework allows for adaptive treatment allocation based on patient response.
    • Demonstrated application in a prostate cancer trial setting.
    • Simulation studies were conducted to evaluate the proposed methods.

    Conclusions:

    • The developed statistical framework provides a more realistic approach to evaluating multi-course cancer treatments.
    • This method increases information yield per patient by incorporating adaptive strategies.
    • The approach is adaptable for trials including toxicity or treatment-related mortality.