A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis
Article first published online: 26 JAN 2011
Copyright © 2011 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 30, Issue 12, pages 1419–1428, 30 May 2011
How to Cite
Tervonen, T., van Valkenhoef, G., Buskens, E., Hillege, H. L. and Postmus, D. (2011), A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis. Statist. Med., 30: 1419–1428. doi: 10.1002/sim.4194
- Issue published online: 10 MAY 2011
- Article first published online: 26 JAN 2011
- Manuscript Accepted: 20 DEC 2010
- Manuscript Received: 15 FEB 2010
- clinical pharmacology;
- decision analysis;
- benefit-risk analysis;
- stochastic multi-criteria accept-ability analysis (SMAA)
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.