INDIRECT AND MIXED TREATMENT COMPARISONS
September 17th - 19th 2012 - Vaughan College, Leicester, UK.
This course is for health economists, statisticians and decision modellers, and systematic reviewers interested in the extension of pair-wise meta-analysis to indirect and mixed treatment comparisons, in the context of either clinical effectiveness or economic evaluation.
The course focuses on Bayesian methods for statistically combining evidence from networks of trials, integrating statistical estimation within a probabilistic modeling framework. The assumptions underlying both pair-wise meta-analysis and mixed treatment comparisons are critically examined. The course also covers methods for detecting and managing heterogeneity and inconsistency.
This is an informal, hands-on course, based on a mixture of lectures and practical work on published datasets using the Bayesian Markov chain Monte Carlo package WinBUGS. Course tutors are available throughout to answer questions and help with exercises.
It is a collaboration between the Department of Health Sciences, University of Leicester and the School of Social and Community Medicine, University of Bristol.
The methods taught on the course were updated in 2011 to be compatible with the NICE 2008 Methods Guide and the Technical Support Documents on Evidence Synthesis (http://www.nicedsu.org.uk), and with the Report of the ISPOR Task Force on Indirect Comparisons.
*Anyone undertaking or managing health technology assessments, including in the context of cost-effectiveness analysis,
*Statisticians, familiar with the principles of meta-analysis, who wish to learn about Bayesian methods for evidence synthesis particularly in the context of cost-effectiveness analysis,
*Anyone responsible for managing systematic reviews.
WHAT YOU WILL LEARN
By the end of the course participants will be able to:
*Conduct pair-wise, indirect comparison and mixed treatment comparison (IC/MTC) evidence synthesis using WinBUGS Bayesian software,
*Adjust for covariates,
*Integrate statistical evidence synthesis with probabilistic cost effectiveness analysis,
*Assess the degree of heterogeneity and inconsistency in RCT data,
*Understand the assumptions and potential pitfalls in pair-wise and IC/MTC meta-analysis,
*Participants will also have an introductory understanding of Bayesian methods, hierarchical modeling, and be able to use WinBUGS software.
Keith Abrams, Tony Ades, Debbi Caldwell, Nicola Cooper, Sofia Dias, Alex Sutton, Nicky Welton
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