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Using covariates to reduce uncertainty in the economic evaluation of clinical trial data

✍ Scribed by F. J. Vázquez-Polo; M. A. Negrín Hernández; B. González López-Valcárcel

Publisher
John Wiley and Sons
Year
2005
Tongue
English
Weight
202 KB
Volume
14
Category
Article
ISSN
1057-9230

No coin nor oath required. For personal study only.

✦ Synopsis

Abstract

As part of their practice, policymakers have to make economic evaluations using clinical trial data. Recent interest has been expressed in determining how cost‐effectiveness analysis can be undertaken in a regression framework. In this respect, published research basically provides a general method for prognostic factor adjustment in the presence of imbalance, emphasizing sub‐group analysis. In this paper, we present an alternative method from a Bayesian approach. We propose the use of covariates in Bayesian health technology assessment in order to reduce uncertainty about the effect of treatments. We show its advantages by comparison with another published method that do not adjust for covariates using simulated data. Copyright © 2004 John Wiley & Sons, Ltd.

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