Linked Life Data

15977288

Source:http://linkedlifedata.com/resource/pubmed/id/15977288

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
21
pubmed:dateCreated
2005-10-13
pubmed:abstractText
In laboratory validation studies, it is often important to assess agreement between two assays, based on different techniques. Oftentimes, both assays have lower limits of detection and thus measurements are left censored. For example, in studies of Human Immunodeficiency Virus (HIV), the branched DNA (bDNA) assay was developed to quantify HIV-1 RNA concentrations in plasma. Validation of newer assays, such as the RT-PCR (reverse transcriptase polymerase chain reaction) involves assessing agreement of measurements obtained using the two techniques. Both bDNA and RT-PCR assays have lower limits of detection and thus new statistical methods are needed for assessing agreement between two left-censored variables. In this paper, we present maximum likelihood and generalized estimating equations approaches to evaluate agreement between two assays that are subject to lower limits of detection. The concordance correlation coefficient is used as an agreement index. The methodology is illustrated using HIV RNA assay data collected as part of a long-term HIV cohort study.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0277-6715
pubmed:author
pubmed:issnType
Print
pubmed:day
15
pubmed:volume
24
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
3347-60
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Assay validation for left-censored data.
pubmed:affiliation
Department of Biostatistics and Bioinformatics, Duke Clinical Research Institute, Duke University, Durham, NC 27715, USA. huiman.barnhart@duke.edu
pubmed:publicationType
Journal Article, Comparative Study, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural