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Related Experiment Videos

An optimal two-stage phase II design utilizing complete and partial response information separately.

Katherine S Panageas1, Alex Smith, Mithat Gönen

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

Controlled Clinical Trials
|August 6, 2002
PubMed
Summary

This study introduces a new two-stage clinical trial design for oncology, distinguishing between complete response and partial response. The proposed multilevel endpoint design improves expected sample size efficiency compared to traditional methods.

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Area of Science:

  • Oncology
  • Clinical Trial Design
  • Biostatistics

Background:

  • Phase II oncology trials assess new treatment efficacy using tumor shrinkage response.
  • Current binary response (complete response/partial response vs. nonresponse) gives equal weight to CR and PR.
  • Complete response (CR) often indicates a more significant antitumor effect and survival benefit than partial response (PR).

Purpose of the Study:

  • To propose a novel two-stage clinical trial design for oncology.
  • To incorporate a multilevel endpoint distinguishing between CR, PR, and nonresponders.
  • To improve upon existing designs like Simon's two-stage design by weighting responses differently.

Main Methods:

  • Developed an extension of Simon's optimal two-stage design.

Related Experiment Videos

  • Utilized a trinomial model to analyze multilevel endpoints (CR, PR, nonresponders).
  • Employed direct search optimization based on exact trinomial probabilities.

    • Main Results:

    • The proposed multilevel endpoint design generally improves expected sample size compared to Simon's design.
    • Design optimization yielded improved efficiency for most evaluated scenarios.
    • Provided sample size tables for common oncologic parameter sets.

    Conclusions:

    • Treating complete response and partial response as distinct outcomes in Phase II oncology trials is advantageous.
    • The proposed trinomial two-stage design offers enhanced sample size efficiency.
    • This approach provides a more nuanced evaluation of therapeutic efficacy in cancer treatment studies.