On the Confidence Intervals in Bioequivalence Studies (2306.06698v1)
Abstract: A bioequivalence study is a type of clinical trial designed to compare the biological equivalence of two different formulations of a drug. Such studies are typically conducted in controlled clinical settings with human subjects, who are randomly assigned to receive two formulations. The two formulations are then compared with respect to their pharmacokinetic profiles, which encompass the absorption, distribution, metabolism, and elimination of the drug. Under the guidance from Food and Drug Administration (FDA), for a size-$\alpha$ bioequivalence test, the standard approach is to construct a $100(1-2\alpha)\%$ confidence interval and verify if the confidence interval falls with the critical region. In this work, we clarify that $100(1-2\alpha)\%$ confidence interval approach for bioequivalence testing yields a size-$\alpha$ test only when the two one-sided tests in TOST are ``equal-tailed''. Furthermore, a $100(1-\alpha)\%$ confidence interval approach is also discussed in the bioequivalence study.
- A new procedure for testing equivalence in comparative bioavailability and other clinical trials. Communications in Statistics-Theory and Methods, 12(23):2663–2692.
- Bioequivalence trials, intersection-union tests and equivalence confidence sets. Statistical Science, 11(4):283–319.
- Optimal confidence sets, bioequivalence, and the limacon of pascal. Journal of the American Statistical Association, 90(431):880–889.
- An unbiased test for the bioequivalence problem. The annals of Statistics, 25(6):2345–2367.
- A survey of the likelihood approach to bioequivalence trials. Statistics in Medicine, 27(24):4874–4894.
- Equivalence testing for functional data with an application to comparing pulmonary function devices. The Annals of Applied Statistics, pages 2002–2026.
- Asymptotical tests on the equivalence, substantial difference and non-inferiority problems with two proportions. Biometrical Journal: Journal of Mathematical Methods in Biosciences, 46(3):305–319.
- Meyners, M. (2012). Equivalence tests–a review. Food quality and preference, 26(2):231–245.
- Union–intersection permutation solution for two-sample equivalence testing. Statistics and Computing, 26(3):693–701.
- Phillips, K. F. (1990). Power of the two one-sided tests procedure in bioequivalence. Journal of pharmacokinetics and biopharmaceutics, 18(2):137–144.
- Bioequivalence: An overview of statistical concepts. Indian Journal of Pharmacology, 36:209–216.
- Romano, J. P. (2005). Optimal testing of equivalence hypotheses. The Annals of Statistics, 33(3):1036–1047.
- Schuirmann, D. (1981). On hypothesis-testing to determine if the mean of a normal-distribution is contained in a known interval. In Biometrics, volume 37, pages 617–617. INTERNATIONAL BIOMETRIC SOC 808 17TH ST NW SUITE 200, WASHINGTON, DC 20006-3910.
- Schuirmann, D. J. (1987). A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability. Journal of pharmacokinetics and biopharmaceutics, 15(6):657–680.
- Efficient estimation of log-normal means with application to pharmacokinetic data. Statistics in medicine, 25(17):3023–3038.
- Checking distributional assumptions for pharmacokinetic summary statistics based on simulations with compartmental models. Journal of Biopharmaceutical Statistics, 27(5):756–772.
- Wellek, S. (2002). Testing statistical hypotheses of equivalence. Chapman and Hall/CRC.
- Westlake, W. (1981). Bioequivalence testing–a need to rethink. Biometrics, 37(3):589–594.
- Westlake, W. J. (1976). Symmetrical confidence intervals for bioequivalence trials. Biometrics, pages 741–744.