Linked Life Data

15823099

Source:http://linkedlifedata.com/resource/pubmed/id/15823099

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2005-4-12
pubmed:abstractText
A quantitative systematic review was performed to estimate the diagnostic accuracy of frozen sections in ovarian tumors. Studies that compared frozen sections and paraffin sections within subjects for diagnosis of ovarian tumors were included. Fourteen primary studies were analyzed, which included 3 659 women. For benign ovarian vs borderline/malignant tumor cases, the occurrence of a positive frozen-section result for benignity (pooled likelihood ratio [LR], 8.7; 95% confidence interval [CI], 7.3-10.4) and posttest probability for benign diagnosis was 95% (95% CI, 94-96%). A positive frozen-section result for malignant vs benign diagnosis (pooled LR, 303; 95% CI, 101-605) increased the probability of ovarian cancer to 98% (95% CI, 97-99%). In borderline vs benign ovarian tumor cases, a positive frozen-section result (pooled LR, 69; 95% CI, 45-106) increased the probability of borderline tumors to 79% (95% CI, 71-85%). In borderline vs malignant ovarian tumor cases, a positive frozen-section result (pooled LR, 18; 95% CI, 13-26) increased the probability of borderline tumors to 51% (95% CI, 42-60%). We conclude that diagnostic accuracy rates for frozen-section analysis is high for malignant and benign ovarian tumors, but the accuracy rates in borderline tumors remain relatively low.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1048-891X
pubmed:author
pubmed:issnType
Print
pubmed:volume
15
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
192-202
pubmed:dateRevised
2006-11-7
pubmed:meshHeading
pubmed:articleTitle
Accuracy of frozen-section analysis in the diagnosis of ovarian tumors: a systematic quantitative review.
pubmed:affiliation
Epidemiology, Federal University of Rio Grande do Sul, Porto Alegre, Brazil. lidia@portoweb.com.br
pubmed:publicationType
Journal Article, Review, Meta-Analysis