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Accuracy of frozen section diagnosis of borderline ovarian tumors.
MedLine Citation:
PMID:  21492922     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
OBJECTIVE: To determine the correlation between the diagnosis of borderline ovarian tumors (BOTs) by frozen section and permanent histology analyses. METHODS: Three hundred fifty-four pathology reports with diagnoses of BOTs by frozen section or permanent histology analysis at a single institution between 1995 and 2010 were evaluated with a review of the literature. Frozen section and permanent histology analyses were compared. Multivariate regression analysis was used to assess the influence of clinicopathological parameters on the likelihood of underdiagnosis. RESULTS: The overall accuracy, i.e., agreement between frozen section and permanent histology diagnoses, was observed in 228 of 354 (64.4%) cases, yielding a sensitivity of 72.6%, a positive predictive value of 85.1%, underdiagnosis in 108 cases (30.5%), and overdiagnosis in 18 cases (5.1%). Based on multivariate analysis, mucinous histology (OR, 1.48; P=0.022) was the only significant predictor for underdiagnosis by frozen section. A comprehensive search of the literature identified 46 studies investigating the accuracy of frozen section analysis of BOTs. The data of 7 of 46 studies that met the criteria for inclusion and the data of the current study were pooled. The overall accuracy was 67.1% (741/1104), yielding a sensitivity of 82.1%, a positive predictive value of 78.7%, underdiagnosis in 222 cases (20.1%), and overdiagnosis in 141 cases (12.8%). CONCLUSIONS: Frozen section analysis of BOTs has low accuracy, sensitivity, and positive predictive value, and underdiagnosis and overdiagnosis are frequent. Therefore, surgical decision-making for BOTs based on frozen section diagnosis should be done carefully, especially in tumors with mucinous histology.
Authors:
Taejong Song; Chel Hun Choi; Ha-Jeong Kim; Min Kyu Kim; Tae-Joong Kim; Jeong-Won Lee; Duk-Soo Bae; Byoung-Gie Kim
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-4-12
Journal Detail:
Title:  Gynecologic oncology     Volume:  -     ISSN:  1095-6859     ISO Abbreviation:  -     Publication Date:  2011 Apr 
Date Detail:
Created Date:  2011-4-15     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0365304     Medline TA:  Gynecol Oncol     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2011 Elsevier Inc. All rights reserved.
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