Comparing a Bayesian Approach (BEST) with the Two One-Sided t-Tests (TOSTs) for Bioequivalence Studies

AbstractThe two one-sidedt-tests (TOST) procedure has been used to evaluate average bioequivalence (BE). As a regulatory standard, it is crucial that TOST distinguish BE from not-BE (NBE) when BE data are not lognormal. TOST was compared with a Bayesian procedure (BEST by Kruschke) in simulated datasets of test/reference ratios (T/R) which were BE and NBE, wherein (1) log(T/R) or T-R were normally distributed, (2) sample sizes ranged 10 –50, and (3) extreme log(T/R) or T-R values were randomly included in datasets. The 90% “credible interval” (CrI) from BEST is a Bayesian alternative of the 90% confidence interval (CI) of TOST and it can be derived from a posterior distribution that is more reflective of the observed mean log (T/R) distribution that often deviates from normality. In the absence of extreme T/R values, both methods agreed BE when observed T/R were lognormal. BEST more accurately concluded BE or NBE, while requiring fewer subjects, when observed log(T/R) or T-R were normal in the presence of extreme values. Overall, TOST and BEST perform comparably on lognormal T/R, while BEST is more accurate, requiring fewer subjects when datasets are normal for T-R or contain extreme values. Of note, the normally distributed datasets only rarely contain extreme values. Our results imply that when BEST and TOST yiel d different BE assessment results from bioequivalent products, TOST may disadvantage applicants when T/R are not lognormal and/or include extreme T/R values....
Source: The AAPS Journal - Category: Drugs & Pharmacology Source Type: research