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.
Econometric Institute, Erasmus University Rotterdam, The Netherlands. tervonen@ese.eur.nl
Tommi
T
Tervonen
Gert
G
van Valkenhoef
Erik
E
Buskens
Hans L
HL
Hillege
Douwe
D
Postmus
D000928:Antidepressive Agents / Q000009:adverse effects / Q000627:therapeutic use; D003657:Decision Making; D003863:Depression / Q000188:drug therapy; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D015233:Models, Statistical; D004364:Pharmaceutical Preparations / Q000592:standards*; D018570:Risk Assessment / Q000379:methods*; D013269:Stochastic Processes
D000928:Antidepressive Agents; D004364:Pharmaceutical Preparations