Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
8
pubmed:dateCreated
2000-9-7
pubmed:abstractText
We have evaluated three alternative models for trisomy 18 screening using the maternal serum markers alpha-fetoprotein (AFP) and intact human chorionic gonadotrophin (hCG). Using data from 46 affected pregnancies and 48 150 unaffected pregnancies, we calculated distribution parameters for AFP and hCG multiples of the median (MoMs) and the factor comprising AFP MoMxhCG MoM. The trisomy 18 risk at mid-trimester was then calculated using either bivariate analysis of AFP and hCG MoMs or univariate analysis of AFP MoMxhCG MoM. The observed detection rates and positive rates obtained using either published distribution parameters or those derived from the West Midlands population were compared for each model. Using fixed cut-offs for AFP and hCG of 0.66 and 0.40 MoMs resulted in a detection rate of 28.3% for a 0.5% false positive rate (FPR). Using published parameters, the univariate analysis model had a slightly higher detection rate of 32.6% for a 0.5% FPR (cut-off 1:248) compared to the bivariate model which was 28.3% (cut-off 1:239). Locally derived distribution parameters significantly improved the detection rate for the bivariate model for FPRs between 0.4-1.3% but worsened it below 0.4%. For the univariate model there was little difference in detection whether local or published parameters were used. Thus, we have confirmed that trisomy 18 screening using two markers can be a worthwhile addition to Down screening.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
0197-3851
pubmed:author
pubmed:copyrightInfo
Copyright 2000 John Wiley & Sons, Ltd.
pubmed:issnType
Print
pubmed:volume
20
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
676-9
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
Maternal serum screening for trisomy 18: assessing different statistical models to optimize detection rates.
pubmed:affiliation
Department of Clinical Chemistry, Birmingham Women's Hospital NHS Trust, Edgbaston, Birmingham B15 2TG, UK. david.kennedy@bham-womens.thenhs.com
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't