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Extinction Training During the Reconsolidation Window Prevents Recovery of Fear
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Continual reassessment designs with early termination.

John O'Quigley1

  • 1Department of Mathematics, University of California at San Diego, La Jolla CA 92093, USA. oquigley@math.ucsd.edu

Biostatistics (Oxford, England)
|August 23, 2003
PubMed
Summary

This study explores simpler stopping rules for the Continual Reassessment Method (CRM) in clinical trials. These rules aim to reduce sample sizes by stopping trials early when the maximum tolerated dose (MTD) is likely found.

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Pharmacometrics

Background:

  • The Continual Reassessment Method (CRM) is a widely used adaptive design for phase I clinical trials to determine the maximum tolerated dose (MTD).
  • Traditional CRM designs often utilize a fixed sample size, potentially leading to larger-than-necessary participant numbers.
  • There is a need for efficient stopping rules to optimize trial duration and resource allocation.

Purpose of the Study:

  • To investigate and simplify stopping rules for the Continual Reassessment Method (CRM).
  • To evaluate the operating characteristics of proposed simpler stopping rules for dose-finding studies.
  • To enhance the efficiency of phase I clinical trials by enabling early termination.

Main Methods:

  • Analysis of existing probabilistic stopping rules for CRM.
  • Development and investigation of a simplified stopping rule based on reaching a stable dose estimate.
  • Simulation studies to assess the performance and operating characteristics of the proposed rules.

Main Results:

  • Existing stopping rules, while effective, are complex to implement.
  • A simpler stopping rule can be developed based on the principle of having reached a definitive dose level.
  • The operating characteristics of these simpler rules warrant deeper investigation.

Conclusions:

  • Simpler stopping rules for CRM could improve the efficiency of phase I dose-finding studies.
  • Further research into the practical implementation and performance of these simplified rules is beneficial.
  • Optimizing trial stopping criteria can lead to reduced sample sizes and faster MTD estimation.