A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis
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.
|Keywords||Benefit-risk analysis, Clinical pharmacology, Decision analysis, Stochastic multi-criteria accept-ability analysis (SMAA)|
|Persistent URL||dx.doi.org/10.1002/sim.4194, hdl.handle.net/1765/23943|
|Journal||Statistics in Medicine|
Tervonen, T, van Valkenhoef, G, Buskens, E, Hillege, H.L, & Postmus, D. (2011). A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis. Statistics in Medicine, 30(12), 1419–1428. doi:10.1002/sim.4194