Linked Life Data

21268053

Source:http://linkedlifedata.com/resource/pubmed/id/21268053

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
2011-5-11
pubmed:abstractText
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.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
1097-0258
pubmed:author
pubmed:copyrightInfo
Copyright © 2011 John Wiley & Sons, Ltd.
pubmed:issnType
Electronic
pubmed:day
30
pubmed:volume
30
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1419-28
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis.
pubmed:affiliation
Econometric Institute, Erasmus University Rotterdam, The Netherlands. tervonen@ese.eur.nl
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't