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Activity Number: 63
Type: Topic Contributed
Date/Time: Sunday, July 31, 2016 : 4:00 PM to 5:50 PM
Sponsor: Biopharmaceutical Section
Abstract #321330
Title: Network Meta-Analysis for Ordinal Outcomes: An Application in Comparing Crohn's Disease Treatments
Author(s): May Mo* and Yeongjin Gwon and Ming-Hui Chen and Amy Xia and Juan Li and Joseph G. Ibrahim
Companies: Amgen and University of Connecticut and University of Connecticut and Amgen and Amgen and The University of North Carolina at Chapel Hill
Keywords: aggregated covariates ; cutoff points ; head-to-head comparisons ; indirect comparisons ; Proportional Odds Model ; random effect
Abstract:

Crohn's Disease is a life-long condition associated with recurrent relapses characterized by abdominal pain, weight loss, anemia, and persistent diarrhea. Currently in the US, there are approximately 780,000 Crohn's disease patients and 33,000 new cases are added each year. In this paper, we propose a new network meta-regression approach for modeling ordinal outcomes in order to assess the efficacy of treatments for Crohn's disease. Specifically, we develop regression models based on aggregate trial-level covariates for the underlying cutoff points of the ordinal outcomes as well as for the variances of the random effects to capture heterogeneity across trials. Our proposed models are particularly useful for indirect comparisons of multiple treatments that have not been compared head-to-head within the network meta-analysis framework. A detailed case study demonstrating the usefulness of the proposed methodology is carried out using aggregate ordinal outcome data from 13 clinical trials for treating Crohn's disease.


Authors who are presenting talks have a * after their name.

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