A flexible Bayesian approach for modeling monotonic dose-response relationships in drug development trials.
Clinical trials often involve comparing 2-4 doses or regimens of an experimental therapy with a control treatment. These studies might occur early in a drug development process, where the aim might be to demonstrate a basic level of proof (the so-called proof of concept (PoC) studies), at a later stage, to help establish a dose or doses that should be used in phase III trials (dose-finding), or even in confirmatory studies, where the registration of several doses might be considered. When a small number of doses are examined, the ability to implement parametric modeling is somewhat limited. As an alternative, in this paper, a flexible Bayesian model is suggested. In particular, we draw on the idea of using Bayesian model averaging (BMA) to exploit an assumed monotonic dose-response relationship, without using strong parametric assumptions. The approach is exemplified by assessing operating characteristics in the design of a PoC study examining a new treatment for psoriatic arthritis and a post hoc data analysis involving three confirmatory clinical trials, which examined an adjunctive treatment for partial epilepsy. Key difficulties, such as prior specification and computation, are discussed. A further extension, based on combining the flexible modeling with a classical multiple comparisons procedure, known as MCP-MOD, is examined. The benefit of this extension is a potential reduction in the number of simulations that might be needed to investigate operating characteristics of the statistical analysis.
a Novartis Pharmaceuticals , East Hanover , New Jersey , USA.
David
D
Ohlssen
Amy
A
Racine
D000704:Analysis of Variance; D000893:Anti-Inflammatory Agents / Q000627:therapeutic use; D000927:Anticonvulsants / Q000627:therapeutic use; D015535:Arthritis, Psoriatic / Q000188:drug therapy; D001499:Bayes Theorem; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D055808:Drug Discovery / Q000706:statistics & numerical data*; D004827:Epilepsy / Q000188:drug therapy; D006801:Humans; D016015:Logistic Models; D015233:Models, Statistical; D016896:Treatment Outcome
D000893:Anti-Inflammatory Agents; D000927:Anticonvulsants
Bayesian model averaging; Dose–response modeling; Evidence synthesis; MCP–MOD; Proof of concept studies