Group-by-treatment interaction effects in comparative bioavailability studies

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Authors

Schuetz, Helmut
Burger, Divan Aristo
Cobo, Erik
Dubins, David D.
Farkas, Tibor
Labes, Detlew
Lang, Benjamin
Ocana, Jordi
Ring, Arne
Shitova, Anastasia

Journal Title

Journal ISSN

Volume Title

Publisher

Springer

Abstract

Comparative bioavailability studies often involve multiple groups of subjects for a variety of reasons, such as clinical capacity limitations. This raises questions about the validity of pooling data from these groups in the statistical analysis and whether a group-by-treatment interaction should be evaluated. We investigated the presence or absence of group-by-treatment interactions through both simulation techniques and a meta-study of well-controlled trials. Our findings reveal that the test falsely detects an interaction when no true group-by-treatment interaction exists. Conversely, when a true group-by-treatment interaction does exist, it often goes undetected. In our meta-study, the detected group-by-treatment interactions were observed at approximately the level of the test and, thus, can be considered false positives. Testing for a group-by-treatment interaction is both misleading and uninformative. It often falsely identifies an interaction when none exists and fails to detect a real one. This occurs because the test is performed between subjects in crossover designs, and studies are powered to compare treatments within subjects. This work demonstrates a lack of utility for including a group-by-treatment interaction in the model when assessing single-site comparative bioavailability studies, and the clinical trial study structure is divided into groups.

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Keywords

Average bioequivalence, Group-by-treatment interaction, Monte-Carlo simulations, Regulatory guidelines

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None

Citation

Schütz, H., Burger, D.A., Cobo, E. et al. Group-by-Treatment Interaction Effects in Comparative Bioavailability Studies. The AAPS Journal 26, 50 (2024). https://doi.org/10.1208/s12248-024-00921-x.