Identifying Potential Adverse Events Dose-Response Relationships via Bayesian Indirect and Mixed Treatment Comparison Models

• Activity Number: 493
• Type: Topic Contributed
• Date/Time: Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Haoda Fu*+ and Karen Price and Mary E. Nilsson and Stephen J. Ruberg
• Companies: and Eli Lilly and Company and Eli Lilly and Company and Eli Lilly and Company
• Keywords: Adverse events ; Bayesian methods ; Dose response ; Hierarchical models ; Indirect comparison ; Meta-analysis

Abstract

To help ensure patient safety for medical products, it is important to assess whether a potential adverse event dose response relationship exists, through combination of all the evidence from multiple clinical trials. The studies that need to be combined often include differing dose levels. Including only the trials with all the common doses for assessment of the dose response relationship will lead to the exclusion of potentially several trials as well as dose arms, thus the loss of information. Bayesian methodology has been shown to be useful in the context of indirect and mixed treatment comparison methods, to combine information from different therapies in different studies in order to make treatment effect inferences. We consider this type of an approach as foundational to the models presented here, but instead in the setting of different dose arms in different studies, by extending the methodology to allow for assessment of the dose response relationship across multiple clinical trials.