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Abstract Details

Activity Number: 602
Type: Topic Contributed
Date/Time: Thursday, August 2, 2012 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section
Abstract - #305014
Title: Use of Bayesian Meta-Analysis Methods to Develop a Tool to Predict the Risk of Stent Thrombosis (ST) Following the Implantation of a Coronary Artery Stent
Author(s): Mark Belger*+ and Fanni Natanegara and Ming-Dauh Wang and Walid Fakhouri and Peita Graham-Clarke
Companies: Eli Lilly and Company and Eli Lilly and Company and Eli Lilly and Company and Eli Lilly and Company and Eli Lilly and Company
Address: 4 The Paddocks, Bristol, BS16 6XG, United Kingdom
Keywords: Bayesian ; HTA ; risk models ; meta-analysis ; informative priors
Abstract:

To obtain reimbursement for a drug, HTA organizations often favor the use of new technologies to assess need in patients who are at high risk. Traditional methods look at developing these risk models from individual trial or registry data; however the results from individual studies often produce conflicting results as to the important factors, or are not large enough to identify all of the important factors needed to develop a risk score. There is a need to synthesize the evidence from these studies and achieve a consensus view on the important risk factors and their associated weightings. We considered a Bayesian meta-analysis approach to this question, illustrating the methods used through the development of a risk score for patients developing ST. A systematic robust questionnaire was developed to capture the opinions of clinical experts and translate them to information that can be included in the Bayesian model, as informative priors. Using a Bayesian framework we were able to combine the data, from 44 studies, with the information from clinical experts, and achieve a consensus on the factors and their associated weightings to include in a tool to predict the risk of ST.


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