Grayling, Michael J., Mander, Adrian P. ORCID: https://orcid.org/0000-0002-0742-9040 and Wason, James M. S. 2019. Two-stage adaptive designs for three-treatment bioequivalence studies. Statistics in Biopharmaceutical Research 11 (4) , pp. 360-374. 10.1080/19466315.2019.1654911 |
Abstract
Bioequivalence (BE) studies are most often conducted as crossover trials, and therefore establishing their required sample size necessitates specification of the within-person variance. Given that this specification is often difficult in practice, there has been great interest in recent years in the use of adaptive designs for BE trials. However, while numerous methods for this have now been presented, their focus has been solely on two-treatment BE studies. In some instances, it will be desired to incorporate more than a single test and reference formulation into a BE trial. It would therefore be useful to establish methodology for the design of adaptive multi-treatment BE trials, to acquire the benefits in the two-treatment setting in this more complex situation. Here, we achieve this for three-treatment studies by extending previously proposed designs for two-treatment trials. First, we discuss the additional design considerations that arise when multiple comparisons are made. Next, an extensive simulation study is employed to compare the performance of the proposed procedures. With this, we demonstrate that two-stage designs with desirable statistical operating characteristics can be readily identified for three-treatment BE trials. Supplementary materials for this article are available online.
Item Type: | Article |
---|---|
Date Type: | Publication |
Status: | Published |
Schools: | Medicine Centre for Trials Research (CNTRR) |
Publisher: | Taylor & Francis: STM, Behavioural Science and Public Health Titles |
ISSN: | 1946-6315 |
Date of Acceptance: | 5 August 2019 |
Last Modified: | 09 Nov 2022 10:50 |
URI: | https://orca.cardiff.ac.uk/id/eprint/140825 |
Citation Data
Cited 2 times in Scopus. View in Scopus. Powered By Scopus® Data
Actions (repository staff only)
Edit Item |