Multiplicity Adjustment Methods for a Three-Way Crossover Bioequivalence Study

For generic drugs, a three-way crossover bioequivalence (BE) study is often used to compare two generic (T) formulations against the common brand-name (R) formulation. Adjustment for multiplicity in equivalence testing, however, is little researched. The new ICH M13A guidance mentioned multiplicity control for equivalence but did not recommend any specific methods. In this paper, we evaluate the applicability of traditional multiplicity adjustment methods in equivalence testing. We propose three revised methods (Bonferroni, Holm, and Hochberg) which are applied on not only p-values but also the more commonly used confidence intervals in equivalence testing. We also apply the 'two-at-a-time' rule as recommended by regulatory agencies and incorporate the correlation among test statistics in simulation. All of these are advances compared to current multiplicity control methods for equivalence. Simulation shows that our proposed methods in a three-way crossover study greatly improve power and reduce needed sample size compared to conducting two two-way crossover studies, control the family-wise error rate at a desired level, and only slightly increase the required sample size compared to no alpha adjustment. Therefore, we recommend our revised Bonferroni, Holm, or Hochberg method in a three-way crossover design when assessing the BE of 2 Ts to 1 R.