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Related Concept Videos

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Sequential continual reassessment method for two-dimensional dose finding.

Ying Yuan1, Guosheng Yin

  • 1Department of Biostatistics, The University of Texas M. D. Anderson Cancer Center, Houston, TX 77030, U.S.A. yyuan@mdanderson.org

Statistics in Medicine
|July 12, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a novel adaptive design for two-dimensional dose finding in clinical trials. The method efficiently reduces sample size while maintaining performance in complex scenarios like multi-drug or dose-schedule optimization.

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Area of Science:

  • Clinical Trials
  • Biostatistics
  • Pharmacology

Background:

  • Traditional single-agent dose-finding methods are inadequate for complex two-dimensional scenarios.
  • Phase I trials often involve simultaneous optimization of multiple agents or dose-schedule combinations.
  • Existing methods face challenges in efficiently navigating the expanded dose-finding space.

Purpose of the Study:

  • To propose a simple and adaptive two-dimensional dose-finding design.
  • To accommodate various single-agent dose-finding methodologies within a unified framework.
  • To reduce sample size requirements and improve efficiency in complex early-phase trials.

Main Methods:

  • Converting two-dimensional dose finding into sequential one-dimensional subtrials.
  • Utilizing line search segments with a fixed dose level for one agent.
  • Employing partial order to eliminate doses outside the search range based on Maximum Tolerated Dose (MTD) findings.

Main Results:

  • The proposed design significantly reduces the sample size needed for two-dimensional dose finding.
  • The method demonstrates good performance in simulation studies.
  • The adaptive approach efficiently shrinks the two-dimensional dose-finding space.

Conclusions:

  • The novel design offers an efficient and effective solution for two-dimensional dose finding in Phase I trials.
  • This approach is applicable to multi-drug trials and dose-schedule optimization.
  • The method provides a practical tool for optimizing complex treatment regimens early in drug development.