Bayesian Indirect and Mixed Treatment Comparisons Across Longitudinal Time Points

• Activity Number: 591
• Type: Topic Contributed
• Date/Time: Wednesday, August 7, 2013 : 2:00 PM to 3:50 PM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): Haoda Fu*+ and Ying Ding
• Companies: and University of Pittsburgh
• Keywords: BEST ; Bayesian methods ; Comparative effectiveness research ; Indirect comparison ; ITP model ; Meta-analysis

Abstract

In this paper, we extend the current indirect comparison methods and propose a Bayesian indirect and mixed treatment comparison longitudinal model. That incorporates multiple time points and allows indirect comparisons of treatment effects across different longitudinal studies. The proposed model only uses summary level longitudinal data. This model is particularly useful when a meta-analysis is performed on studies with different durations. It enables the borrowing of information from shorter studies even in the situation where the primary interest is in a time point beyond the duration of some these shorter studies. Simulation studies were performed which demonstrate that the proposed method performs well and yields better estimations compared to other single time point meta-analysis methods. We apply our method to a set of studies from patients with type 2 diabetes.