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Optimal adaptive sequential designs for crossover bioequivalence studies
Author(s) -
Xu Jialin,
Audet Charles,
DiLiberti Charles E.,
Hauck Walter W.,
Montague Timothy H,
Parr Alan F.,
Potvin Diane,
Schuirmann Donald J.
Publication year - 2015
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.1721
Subject(s) - bioequivalence , sequential analysis , crossover , sample size determination , statistics , mathematics , crossover study , adaptive design , type i and type ii errors , nominal level , computer science , mathematical optimization , confidence interval , medicine , machine learning , clinical trial , placebo , alternative medicine , pathology , pharmacology , bioavailability
In prior works, this group demonstrated the feasibility of valid adaptive sequential designs for crossover bioequivalence studies. In this paper, we extend the prior work to optimize adaptive sequential designs over a range of geometric mean test/reference ratios (GMRs) of 70–143% within each of two ranges of intra‐subject coefficient of variation (10–30% and 30–55%). These designs also introduce a futility decision for stopping the study after the first stage if there is sufficiently low likelihood of meeting bioequivalence criteria if the second stage were completed, as well as an upper limit on total study size. The optimized designs exhibited substantially improved performance characteristics over our previous adaptive sequential designs. Even though the optimized designs avoided undue inflation of type I error and maintained power at ≥ 80%, their average sample sizes were similar to or less than those of conventional single stage designs. Copyright © 2015 John Wiley & Sons, Ltd.