Joint modeling of clinical efficacy and safety with an application to diabetes studies

The purpose of drug development is to evaluate a drug's efficacy and safety profile. For a personalized medicine, it is important for patients and health care providers to understand the efficacy and safety trade-off when selecting a dose for a patient. In this article, we propose three different methods for jointly modeling the clinical safety and efficacy endpoints. These three methods model the correlation relationship in three different ways: modeling the joint distribution by a copula method, modeling conditional distributions, and modeling their correlations through individual means by a hierarchical model. We compare these three methods through simulations and apply these methods to a data set from a diabetes study.