The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Online Program Home
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.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2012 program
|
2012 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.