Academic Journal
Group-by-Treatment Interaction Effects in Comparative Bioavailability Studies
| Title: | Group-by-Treatment Interaction Effects in Comparative Bioavailability Studies |
|---|---|
| Authors: | Helmut Schütz, Divan A. Burger, Erik Cobo, David D. Dubins, Tibor Farkás, Detlew Labes, Benjamin Lang, Jordi Ocaña, Arne Ring, Anastasia Shitova, Volodymyr Stus, Michael Tomashevskiy |
| Contributors: | Universitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa, Universitat Politècnica de Catalunya. GRBIO - Grup de Recerca en Bioestadística i Bioinformàtica |
| Source: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) |
| Publisher Information: | Springer Science and Business Media LLC, 2024. |
| Publication Year: | 2024 |
| Subject Terms: | Biometry, Biomatemàtica, Classificació AMS::62 Statistics::62D05 Sampling theory, sample surveys, Biological Availability, Classificació AMS::92 Biology and other natural sciences::92B Mathematical biology in general, regulatory guidelines, Monte-Carlo simulations, Cross-Over Studies [MeSH], Humans [MeSH], group-by-treatment interaction, average bioequivalence, Biological Availability [MeSH], Research Design [MeSH], Research Article, 01 natural sciences, Classificació AMS::62 Statistics::62P Applications, sample surveys, 03 medical and health sciences, 0302 clinical medicine, Classificació AMS::62 Statistics::62D05 Sampling theory, Humans, Sampling (Statistics), 0101 mathematics, Group-by-treatment interaction, Biomathematics, Biometria, Cross-Over Studies, Average bioequivalence, Àrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències, Research Design, Regulatory guidelines, Mostreig (Estadística) |
| Description: | 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. Graphical Abstract |
| Document Type: | Article |
| File Description: | application/pdf |
| Language: | English |
| ISSN: | 1550-7416 |
| DOI: | 10.1208/s12248-024-00921-x |
| Access URL: | https://pubmed.ncbi.nlm.nih.gov/38632178 https://hdl.handle.net/2117/409494 https://doi.org/10.1208/s12248-024-00921-x https://repository.publisso.de/resource/frl:6508400 |
| Rights: | CC BY |
| Accession Number: | edsair.doi.dedup.....abc4964d28fcbd79e5f2129761bdbe8e |
| Database: | OpenAIRE |
| ISSN: | 15507416 |
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| DOI: | 10.1208/s12248-024-00921-x |