Estimating the predictive validity of diabetic animal models in rosiglitazone studies

Abstract

For therapeutic studies, predictive validity of animal models - arguably the most important feature of animal models in terms of human relevance - can be calculated retrospectively by obtaining data on treatment efficacy from human and animal trials. Using rosiglitazone as a case study, we aim to determine the predictive validity of animal models of diabetes, by analyzing which models perform most similarly to humans during rosiglitazone treatment in terms of changes in standard diabetes diagnosis parameters (glycosylated hemoglobin (HbA1c) and fasting glucose levels). A further objective of this article is to explore the impact of four covariates on the predictive capacity: i) diabetes induction method, ii) drug administration route, iii) sex of animals, and iv) diet during the experiments.