The challenge of incorporating external evidence in trial-based cost-effectiveness analyses: the use of resampling methods
AbstractCost-effectiveness analyses (CEAs) that use patient-specific data on costs and health outcomes from a randomized controlled trial (RCT) are popular, yet such CEAs are often criticized because they neglect to incorporate evidence external to the trial. Although evidence directly defined on cost and health outcomes is often not transferrable across jurisdictions, evidence on biologic aspects of treatments such as the treatment effect can be transferred, and incorporating such evidence in the CEA can conceivably affect the results. Fully parametric Bayesian evidence synthesis for RCTbased CEAs is possible, but there are challenges involved in parametric modeling of cost and health outcomes and their relation with external evidence. A popular method for quantifying uncertainty in a RCT-based CEA is the bootstrap. It will be attractive to further expand this method for the incorporation of external evidence. To this end, we utilize the Bayesian interpretation of the bootstrap and derive the distribution for the cost and effectiveness outcomes after observing the current RCT data and the external evidence. We propose simple modifications of the bootstrap for sampling from such posterior distributions. We use data from a clinical trial and incorporate external evidence on the effect size of treatments to illustrate the method in action. Compared to the parametric models of evidence synthesis, the proposed approach requires fewer distributional assumptions, does not require explicit modeling of the relation between external evidence and outcomes of interest, and is generally easier to implement.
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Bibliographic InfoPaper provided by HEDG, c/o Department of Economics, University of York in its series Health, Econometrics and Data Group (HEDG) Working Papers with number 12/24.
Date of creation: Aug 2012
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Web page: http://www.york.ac.uk/res/herc/research/hedg/
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Cost-Benefit Analysis+ Bayes Theorem+ Clinical Trial+ Statistics; Nonparametric;
Find related papers by JEL classification:
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
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- Elisabeth Fenwick & Karl Claxton & Mark Sculpher, 2001. "Representing uncertainty: the role of cost-effectiveness acceptability curves," Health Economics, John Wiley & Sons, Ltd., vol. 10(8), pages 779-787.
- Glick, Henry A & Doshi, Jalpa A & Sonnad, Seema S & Polsky, Daniel, 2007. "Economic Evaluation in Clinical Trials," OUP Catalogue, Oxford University Press, number 9780198529972.
- Drummond, Michael F. & Sculpher, Mark J. & Torrance, George W. & O'Brien, Bernie J. & Stoddart, Greg L., 2005. "Methods for the Economic Evaluation of Health Care Programmes," OUP Catalogue, Oxford University Press, edition 3, number 9780198529453.
- Andrew H. Briggs & David E. Wonderling & Christopher Z. Mooney, 1997. "Pulling cost-effectiveness analysis up by its bootstraps: A non-parametric approach to confidence interval estimation," Health Economics, John Wiley & Sons, Ltd., vol. 6(4), pages 327-340.
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