Linked Life Data

15613948

Source:http://linkedlifedata.com/resource/pubmed/id/15613948

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2004-12-22
pubmed:abstractText
Costs can hamper the evaluation of the effectiveness of new biomarkers. Analysis of smaller numbers of pooled specimens has been shown to be a useful cost-cutting technique. The Youden index (J), a function of sensitivity (q) and specificity (p), is a commonly used measure of overall diagnostic effectiveness. More importantly, J is the maximum vertical distance or difference between the ROC curve and the diagonal or chance line; it occurs at the cut-point that optimizes the biomarker's differentiating ability when equal weight is given to sensitivity and specificity. Using the additive property of the gamma and normal distributions, we present a method to estimate the Youden index and the optimal cut-point, and extend its applications to pooled samples. We study the effect of pooling when only a fixed number of individuals are available for testing, and pooling is carried out to save on the number of assays. We measure loss of information by the change in root mean squared error of the estimates of the optimal cut-point and the Youden index, and we study the extent of this loss via a simulation study. In conclusion, pooling can result in a substantial cost reduction while preserving the effectiveness of estimators, especially when the pool size is not very large.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
1044-3983
pubmed:author
pubmed:issnType
Print
pubmed:volume
16
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
73-81
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Optimal cut-point and its corresponding Youden Index to discriminate individuals using pooled blood samples.
pubmed:affiliation
Division of Epidemiology, Statistics and Prevention Research, National Institute of Child Health and Human Development, National Institutes of Health, DHHS, Bethesda, Maryland, USA. schistee@mail.nih.gov
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.