A state-of-the-art multi-criteria model for drug benefit-risk analysis

Drug benefit-risk analysis is based on firm clinical evidence related to various safety and efficacy outcomes, such as tolerability, treatment response, and adverse events. In this paper, we propose a new approach for constructing a supporting multi-criteria model that fully takes into account this evidence. Our approach is based on the Stochastic Multicriteria Acceptability Analysis (SMAA) methodology, which allows us to compute the typical value judgments that support a decision, to quantify uncertainty, and to compute a comprehensive benefit-risk profile. As an example, we constructed a multi-criteria model for the therapeutic group of second-generation antidepressants. We analyzed Fluoxetine, Paroxetine, Sertraline, and Venlafaxine according to relative efficacy and absolute rates of several common adverse drug reactions using meta-analytical data from the literature. Our model showed that there are clear trade-offs among the four drugs. Based on our experiences from this study, SMAA appears to be a suitable approach for quantifying trade-offs and decision uncertainty in drug benefit-risk analysis.