title: Joint modeling of clinical efficacy and safety with an application to diabetes studies.
abstract: 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.
authors: Department of Statistics, University of Wisconsin-Madison, Madison, Wisconsin, USA.
authors: Yang
authors: Y
authors: Zhao
authors: Wei
authors: W
authors: Shen
authors: Haoda
authors: H
authors: Fu
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D055808:Drug Discovery / Q000379:methods / Q000706:statistics & numerical data*; D023381:Endpoint Determination / Q000379:methods / Q000706:statistics & numerical data*; D006801:Humans; D007004:Hypoglycemic Agents / Q000008:administration & dosage / Q000009:adverse effects / Q000627:therapeutic use; D015233:Models, Statistical; D012107:Research Design / Q000592:standards / Q000706:statistics & numerical data*; D016896:Treatment Outcome
chemical_list: D007004:Hypoglycemic Agents