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Sample sizes for event rate equivalence trials using prior information

A L Gould1

  • 1Merck Research Laboratories, West Point, PA 19486.

Statistics in Medicine
|November 15, 1993
PubMed
Summary
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Calculating sample sizes for treatment equivalence trials requires careful consideration of event rates and uncertainty. Bayesian methods can improve accuracy by incorporating data from prior studies, ensuring adequate sample size for reliable results.

Area of Science:

  • Clinical Trials
  • Biostatistics
  • Pharmacoeconomics

Background:

  • Equivalence trials, comparing standard and test treatments, often need large sample sizes.
  • Sample size determination relies on defining 'equivalence' and estimating the overall event rate, which introduces uncertainty.

Purpose of the Study:

  • To explore methods for sample size calculation in equivalence trials.
  • To address the uncertainty in estimating the overall event rate for sample size planning.

Main Methods:

  • Utilizing Bayesian and Empirical Bayes statistical methods.
  • Incorporating data from previous clinical trials into sample size calculations.

Main Results:

  • Bayesian approaches can enhance sample size calculations by leveraging historical data.

Related Experiment Videos

  • These methods provide a framework for achieving high confidence in equivalence when the event rate ratio is below a specified threshold.

    • Conclusions:

    • Bayes and Empirical Bayes methods offer a robust approach to sample size determination in equivalence trials.
    • These statistical techniques help manage uncertainty and ensure adequate power for demonstrating treatment equivalence.