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Date
Jun
06
2006

Cost-Effectiveness Analysis under Uncertainty: Investigating the Role of the Cost-Effectiveness Frontier (CEF)

Presenter:

Gary Zarkin

Authors:

Gary Zarkin, Jeremy Bray, Debanjali Mitra, Mohan Bala, David Couper

Chair: James Burgess; Discussant: TBA Tue June 6, 2006 8:00-9:30 Room 121

Rationale: Several methods of handling uncertainty of cost-effectiveness ratios exist. A limitation of these methods is that they do not adequately address the uncertainty associated with interventions being dominated. If an intervention is dominated in either a strong (greater cost and lower effectiveness) or weak sense (greater cost-effectiveness ratio), it is no longer included in the cost-effectiveness frontier and it drops out of further cost-effectiveness analysis. Existing methods of dealing with uncertainty in CE ratios do not adequately incorporate variability in the CEF.

Objectives: The objective of this methodological paper is to introduce uncertainty of the CEF into cost-effectiveness analysis. The paper lays out the methodology that researchers should follow to address uncertainty in the CEF. We demonstrate how this uncertainty changes the typical cost-effectiveness analysis.

Methodology: We assume that the cost and effectiveness realizations for each intervention arm are drawn from a bivariate normal (BVN) distribution. We draw a cost and effectiveness pair from each BVN distribution and calculate the implied CEF. We draw N=1000 draws for each intervention arm and calculate the implied CEF for each draw. Based on these outcomes, we calculate the probability associated with each realization of the CEF.

We propose to use cost and effectiveness data from the COMBINE trial to estimate the parameters for the BVN distribution. These parameters include the mean cost, mean effectiveness (measured by days heavy drinking), the standard deviation of cost and effectiveness, and the correlation of cost and effectiveness for each of the 9 arms of the COMBINE trial. An advantage of using the COMBINE data is that it provides an anchor to actual clinical trial, which increases the relevance of the analyses.

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