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Optimal two-stage design for a series of pilot trials of new agents

T J Yao1, E S Venkatraman

  • 1Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York 10021, USA. yao@biost.mskcc.org

Biometrics
|September 29, 1998
PubMed

Insights

This study refines sample size calculations for therapeutic agent screening trials using a two-stage design. It confirms that smaller screening trials are optimal for efficiently identifying promising new treatments.

Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Pharmacological Research

Background:

  • Traditional screening trials face challenges in optimizing sample size and time for identifying therapeutic agents.
  • Previous work by Yao, Begg, and Livingston (1996) established an approach for sample size determination in screening trials.

Purpose of the Study:

  • To improve upon existing methods for determining sample sizes in therapeutic agent screening.
  • To introduce a two-stage design that minimizes the time to identify promising agents while maintaining fixed error rates.

Main Methods:

  • Development of a two-stage adaptive design for screening trials.
  • Application of the improved methodology to historical data from exploratory vaccination trials.
  • Utilizing bootstrap methods to evaluate the reliability of the findings.

Main Results:

  • The two-stage design effectively minimizes the time required to identify promising therapeutic agents.
  • Analysis of historical data indicates that smaller individual screening trials are optimal.
  • Bootstrap evaluation confirmed the robustness and reliability of the proposed method.

Conclusions:

  • The enhanced two-stage design offers a more efficient approach to therapeutic agent screening.
  • Optimizing sample size through smaller, sequential trials is recommended for improved efficiency.
  • This methodology provides a reliable framework for future drug discovery and development efforts.

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