Complementing information from incremental net benefit: A Bayesian perspective

Abstract

Cost-effectiveness analysis of a treatment is typically based on specific functions of the expectation of the effectiveness and cost of the treatment, and treatment comparisons are made in the same vein. The mathematical expectation has been the cornerstone for defining the incremental cost-effectiveness ratio and the incremental net benefit, the most popular tools for cost-effectiveness analysis for pairwise treatment comparisons. In this paper we propose a framework for cost-effectiveness analysis based on the whole posterior distribution of effectiveness and cost. We adopt a Bayesian perspective and use the predictive posterior distribution of the net benefit. The analysis based on the whole posterior distribution captures the uncertainty about the value of effectiveness and cost of the treatment and overcomes some limitations presented by the mean, as a summary measure, when skewed data are considered. Furthermore, it allows us to compare more than two treatments. An illustration with real data is provided.