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Diagnostic accuracy of frozen section analysis of borderline ovarian tumors: a meta-analysis with emphasis on misdiagnosis factors
Objective: First, to evaluate the sensitivity and positive predictive value (PPV) of intra-operative frozen section (FS) diagnosis in borderline ovarian tumors (BOTs), and to explore the factors affecting the diagnostic accuracy. Second, to assess the clinical outcomes of misdiagnosed BOT patients....
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Ivyspring International Publisher
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6096369/ https://www.ncbi.nlm.nih.gov/pubmed/30123350 http://dx.doi.org/10.7150/jca.25883 |
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author | Huang, Zhen Li, Li Li, ChengCheng Ngaujah, Samuel Yao, Shu Chu, Ran Xie, Lin Yang, XingSheng Zhang, Xiangning Liu, Peishu Jiang, Jie Zhang, Youzhong Cui, Baoxia Song, Kun Kong, Beihua |
author_facet | Huang, Zhen Li, Li Li, ChengCheng Ngaujah, Samuel Yao, Shu Chu, Ran Xie, Lin Yang, XingSheng Zhang, Xiangning Liu, Peishu Jiang, Jie Zhang, Youzhong Cui, Baoxia Song, Kun Kong, Beihua |
author_sort | Huang, Zhen |
collection | PubMed |
description | Objective: First, to evaluate the sensitivity and positive predictive value (PPV) of intra-operative frozen section (FS) diagnosis in borderline ovarian tumors (BOTs), and to explore the factors affecting the diagnostic accuracy. Second, to assess the clinical outcomes of misdiagnosed BOT patients. Methods: We performed a retrospective study of all patients diagnosed as BOT through FS or paraffin section (PS) at Qilu Hospital between January 2005 and December 2015. Clinical and pathologic data were extracted. Univariate analysis was performed using standard two-sided statistical tests. We also performed a meta-analysis to further validate the findings. Results: In our retrospective study, 155 patients were included. Agreement between FS and PS diagnosis was observed in 127/155 (81.9%) patients, yielding a sensitivity of 92.7% and a PPV of 87.6%. Under-diagnosis and over-diagnosis occurred in 22 cases (14.2%) and 6 cases (3.9%), respectively. In our univariate analysis of our retrospective study, tumor size (p=0.048) and surgery approach (p=0.024) were significantly associated with misdiagnosis. The pooled analysis of 13 studies including 1,577 patients indicated that the accuracy (69.2%), sensitivity (82.5%), and PPV (81.1%) were low; also under-diagnosis (20.2%) and over-diagnosis (10.5%) were frequent. The meta-analysis results showed that mucinous histology (p < 0.0001, OR=2.03 [1.47-2.81]) and unilateral tumors (p=0.001, OR=2.39 [1.41-4.06]) were associated with the misdiagnosis of BOT. In our retrospective study, there was no statistical significance of clinical outcome such as extent of surgery (p=0.838), recurrence (p=0.586), fertility (p=0.560), death (p=0.362) between misdiagnosed and accurately diagnosed BOT patients. Conclusions: FS analysis of BOTs has low accuracy, sensitivity, and PPV. Under-diagnosis and over-diagnosis are frequent. Meta-analysis results verify that mucinous histology and unilateral tumors are associated with misdiagnosis of FS. Nevertheless, misdiagnosed patients have a good clinical outcome despite the high frequency of misdiagnosis through FS. |
format | Online Article Text |
id | pubmed-6096369 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Ivyspring International Publisher |
record_format | MEDLINE/PubMed |
spelling | pubmed-60963692018-08-17 Diagnostic accuracy of frozen section analysis of borderline ovarian tumors: a meta-analysis with emphasis on misdiagnosis factors Huang, Zhen Li, Li Li, ChengCheng Ngaujah, Samuel Yao, Shu Chu, Ran Xie, Lin Yang, XingSheng Zhang, Xiangning Liu, Peishu Jiang, Jie Zhang, Youzhong Cui, Baoxia Song, Kun Kong, Beihua J Cancer Research Paper Objective: First, to evaluate the sensitivity and positive predictive value (PPV) of intra-operative frozen section (FS) diagnosis in borderline ovarian tumors (BOTs), and to explore the factors affecting the diagnostic accuracy. Second, to assess the clinical outcomes of misdiagnosed BOT patients. Methods: We performed a retrospective study of all patients diagnosed as BOT through FS or paraffin section (PS) at Qilu Hospital between January 2005 and December 2015. Clinical and pathologic data were extracted. Univariate analysis was performed using standard two-sided statistical tests. We also performed a meta-analysis to further validate the findings. Results: In our retrospective study, 155 patients were included. Agreement between FS and PS diagnosis was observed in 127/155 (81.9%) patients, yielding a sensitivity of 92.7% and a PPV of 87.6%. Under-diagnosis and over-diagnosis occurred in 22 cases (14.2%) and 6 cases (3.9%), respectively. In our univariate analysis of our retrospective study, tumor size (p=0.048) and surgery approach (p=0.024) were significantly associated with misdiagnosis. The pooled analysis of 13 studies including 1,577 patients indicated that the accuracy (69.2%), sensitivity (82.5%), and PPV (81.1%) were low; also under-diagnosis (20.2%) and over-diagnosis (10.5%) were frequent. The meta-analysis results showed that mucinous histology (p < 0.0001, OR=2.03 [1.47-2.81]) and unilateral tumors (p=0.001, OR=2.39 [1.41-4.06]) were associated with the misdiagnosis of BOT. In our retrospective study, there was no statistical significance of clinical outcome such as extent of surgery (p=0.838), recurrence (p=0.586), fertility (p=0.560), death (p=0.362) between misdiagnosed and accurately diagnosed BOT patients. Conclusions: FS analysis of BOTs has low accuracy, sensitivity, and PPV. Under-diagnosis and over-diagnosis are frequent. Meta-analysis results verify that mucinous histology and unilateral tumors are associated with misdiagnosis of FS. Nevertheless, misdiagnosed patients have a good clinical outcome despite the high frequency of misdiagnosis through FS. Ivyspring International Publisher 2018-07-16 /pmc/articles/PMC6096369/ /pubmed/30123350 http://dx.doi.org/10.7150/jca.25883 Text en © Ivyspring International Publisher This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/). See http://ivyspring.com/terms for full terms and conditions. |
spellingShingle | Research Paper Huang, Zhen Li, Li Li, ChengCheng Ngaujah, Samuel Yao, Shu Chu, Ran Xie, Lin Yang, XingSheng Zhang, Xiangning Liu, Peishu Jiang, Jie Zhang, Youzhong Cui, Baoxia Song, Kun Kong, Beihua Diagnostic accuracy of frozen section analysis of borderline ovarian tumors: a meta-analysis with emphasis on misdiagnosis factors |
title | Diagnostic accuracy of frozen section analysis of borderline ovarian tumors: a meta-analysis with emphasis on misdiagnosis factors |
title_full | Diagnostic accuracy of frozen section analysis of borderline ovarian tumors: a meta-analysis with emphasis on misdiagnosis factors |
title_fullStr | Diagnostic accuracy of frozen section analysis of borderline ovarian tumors: a meta-analysis with emphasis on misdiagnosis factors |
title_full_unstemmed | Diagnostic accuracy of frozen section analysis of borderline ovarian tumors: a meta-analysis with emphasis on misdiagnosis factors |
title_short | Diagnostic accuracy of frozen section analysis of borderline ovarian tumors: a meta-analysis with emphasis on misdiagnosis factors |
title_sort | diagnostic accuracy of frozen section analysis of borderline ovarian tumors: a meta-analysis with emphasis on misdiagnosis factors |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6096369/ https://www.ncbi.nlm.nih.gov/pubmed/30123350 http://dx.doi.org/10.7150/jca.25883 |
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