A stochastic multicriteria model for evidence‐based decision making in drug benefit‐risk analysis

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Abstract
Drug benefit‐risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multi‐criteria model that fully takes into account the evidence on efficacy and adverse drug reactions. Our approach is based on the stochastic multi‐criteria acceptability analysis methodology, which allows us to compute the typical value judgments that support a decision, to quantify decision uncertainty, and to compute a comprehensive BR profile. We construct a multi‐criteria model for the therapeutic group of second‐generation antidepressants. We assess fluoxetine and venlafaxine together with placebo according to incidence of treatment response and three common adverse drug reactions by using data from a published study. Our model shows that there are clear trade‐offs among the treatment alternatives. Copyright © 2011 John Wiley & Sons, Ltd.

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