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

• Published in: Statistics in medicine 2011-05, Vol.30 (12), p.1419-1428
• Main Authors: Tervonen, Tommi, van Valkenhoef, Gert, Buskens, Erik, Hillege, Hans L., Postmus, Douwe
• Format: Article
• Language: English
• Subjects: Acceptability; Antidepressants; Antidepressive Agents - adverse effects; Antidepressive Agents - therapeutic use; benefit-risk analysis; clinical pharmacology; decision analysis; Decision Making; Depression - drug therapy; Drug-Related Side Effects and Adverse Reactions; Drugs; Humans; Judgment; Medical treatment; Models, Statistical; Multiple criteria decision making; Pharmaceutical Preparations - standards; Risk assessment; Risk Assessment - methods; Side effects; Stochastic models; stochastic multi-criteria accept-ability analysis (SMAA); Stochastic Processes
• ISSN: 0277-6715; 1097-0258; 1097-0258
• DOI: 10.1002/sim.4194

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.