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

Stat Med. 2011 May 30;30(12):1419-28. doi: 10.1002/sim.4194. Epub 2011 Jan 26.

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antidepressive Agents / adverse effects
  • Antidepressive Agents / therapeutic use
  • Decision Making*
  • Depression / drug therapy
  • Drug-Related Side Effects and Adverse Reactions*
  • Humans
  • Models, Statistical*
  • Pharmaceutical Preparations / standards*
  • Risk Assessment / methods*
  • Stochastic Processes

Substances

  • Antidepressive Agents
  • Pharmaceutical Preparations