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Controlling type 1 error rate for sequential, bioequivalence studies with crossover designs.

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Sample size reestimation in bioequivalence studies can inflate type 1 errors. This study proposes a new variability estimator to prevent type 1 error inflation in crossover bioequivalence trials.

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Area of Science:

  • Biostatistics
  • Pharmacokinetics
  • Clinical Trial Design

Background:

  • Adaptive designs, including sample size reestimation, are valuable in bioequivalence studies when drug variability is unknown.
  • Using pooled estimates for intrasubject variability in conjunction with interim estimates can lead to type 1 error inflation.

Purpose of the Study:

  • To characterize type 1 error inflation in crossover bioequivalence studies with sample size reestimation.
  • To propose a novel estimator for intrasubject variability that corrects for bias and prevents type 1 error inflation.

Main Methods:

  • Extending the characterization of pooled estimator bias from parallel studies to crossover designs.
  • Developing and evaluating a new estimator for intrasubject variability in the context of adaptive crossover bioequivalence trials.

Main Results:

  • The pooled estimate of intrasubject variability is a biased estimator in crossover bioequivalence studies with sample size reestimation.
  • This bias leads to inflation of the type 1 error rate.

Conclusions:

  • Sample size reestimation in crossover bioequivalence studies requires careful consideration of variability estimation.
  • The proposed estimator effectively prevents type 1 error inflation, ensuring the integrity of bioequivalence testing.