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A rank-based sample size method for multiple outcomes in clinical trials.

Peng Huang1, Robert F Woolson, Peter C O'Brien

  • 1Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, SC, USA. huangp@musc.edu

Statistics in Medicine
|January 15, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for calculating sample sizes in clinical trials with multiple outcomes using O'Brien's global test. The approach ensures robust statistical power and accurate type I error control, enhancing trial design.

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Statistical Methods

Background:

  • O'Brien's rank-sum test provides a global assessment of treatment effects across multiple outcomes.
  • Existing methods for sample size calculation in multi-outcome trials require refinement for robustness and efficiency.

Purpose of the Study:

  • To develop a sample size computation method for clinical trials analyzing multiple primary outcomes.
  • To introduce and compute a Global Treatment Effect (GTE) measure for summarizing treatment efficacy.
  • To provide sample size formulas robust to data transformations, outliers, and skewed distributions.

Main Methods:

  • Development of sample size calculation methods based on a prespecified Global Treatment Effect (GTE).
  • Introduction of the Global Treatment Effect (GTE) as a summary measure for multi-outcome efficacy.
  • Derivation of sample size formulas invariant to monotone transformations and robust to outliers and skewed data.

Main Results:

  • Sample size formulas are presented for cases with and without pilot data, including optimal randomization ratios.
  • The proposed method demonstrates robust control of type I error and statistical power through simulations.
  • Comparison with Bonferroni adjustment highlights the advantages of the new sample size method.

Conclusions:

  • The developed sample size method effectively supports clinical trial designs with multiple primary outcomes.
  • The Global Treatment Effect (GTE) offers a reliable measure for summarizing treatment efficacy.
  • The method's robustness and the provision of Splus code facilitate practical application in trial design, including Parkinson's disease studies.