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Diagnostic performance of a nomogram incorporating cribriform morphology for the prediction of adverse pathology in prostate cancer at radical prostatectomy

The aim of the present study was to develop a novel nomogram that incorporated clinical factors, imaging parameters and biopsy pathological factors (including cribriform morphology) to predict adverse pathology in prostate cancer (PCa). A total of 223 patients with PCa, who had undergone preoperativ...

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Autores principales: Wang, Baojun, Gao, Jie, Zhang, Qing, Fu, Yao, Liu, Guangxiang, Zhang, Chengwei, Wei, Wang, Huang, Haifeng, Shi, Jiong, Li, Danyan, Guo, Hongqian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7400272/
https://www.ncbi.nlm.nih.gov/pubmed/32782597
http://dx.doi.org/10.3892/ol.2020.11861
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author Wang, Baojun
Gao, Jie
Zhang, Qing
Fu, Yao
Liu, Guangxiang
Zhang, Chengwei
Wei, Wang
Huang, Haifeng
Shi, Jiong
Li, Danyan
Guo, Hongqian
author_facet Wang, Baojun
Gao, Jie
Zhang, Qing
Fu, Yao
Liu, Guangxiang
Zhang, Chengwei
Wei, Wang
Huang, Haifeng
Shi, Jiong
Li, Danyan
Guo, Hongqian
author_sort Wang, Baojun
collection PubMed
description The aim of the present study was to develop a novel nomogram that incorporated clinical factors, imaging parameters and biopsy pathological factors (including cribriform morphology) to predict adverse pathology in prostate cancer (PCa). A total of 223 patients with PCa, who had undergone preoperative multi-parametric magnetic resonance imaging and had a biopsy of Gleason pattern (GP) 4, absence of GP 5 and pure Grade Group (GG) 3 [Gleason score (GS) 3+4, GS 4+3, GS 4+4], were retrospectively enrolled onto the study. The contribution of GG to the biopsy and Prostate Imaging Reporting and Data System (PI-RADS) score for PCa harboring adverse pathology were analyzed. Univariate and multivariate logistic regression analyses were performed to determine significant pathology predictors of adverse pathology for nomogram development. The nomogram was internally validated using bootstrapping with 1,000 iterations. The diagnostic performance of the nomogram was analyzed by receiver operating characteristics (ROC) analysis and decision curve analysis (DCA). A higher biopsy GG and PI-RADS score were associated with an increased likelihood of adverse pathology. Prostate specific antigen density (PSAD), biopsy GG, cribriform morphology on biopsy and PI-RADS score were significant predictors and were included in the nomogram. The ROC area under the curve of the nomogram was 0.88 (95% confidence interval, 0.84–0.91), with a high specificity (0.91) and moderate sensitivity (0.72). The novel nomogram was shown to have a higher net benefit for the prediction of adverse pathology in PCa, compared with any individual factors determined by DCA. Overall, a novel nomogram incorporating PSAD, PI-RADS score, biopsy GG and cribriform morphology on biopsy was shown to perform well in the prediction of PCa harboring adverse pathology at the time of radical prostatectomy.
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spelling pubmed-74002722020-08-10 Diagnostic performance of a nomogram incorporating cribriform morphology for the prediction of adverse pathology in prostate cancer at radical prostatectomy Wang, Baojun Gao, Jie Zhang, Qing Fu, Yao Liu, Guangxiang Zhang, Chengwei Wei, Wang Huang, Haifeng Shi, Jiong Li, Danyan Guo, Hongqian Oncol Lett Articles The aim of the present study was to develop a novel nomogram that incorporated clinical factors, imaging parameters and biopsy pathological factors (including cribriform morphology) to predict adverse pathology in prostate cancer (PCa). A total of 223 patients with PCa, who had undergone preoperative multi-parametric magnetic resonance imaging and had a biopsy of Gleason pattern (GP) 4, absence of GP 5 and pure Grade Group (GG) 3 [Gleason score (GS) 3+4, GS 4+3, GS 4+4], were retrospectively enrolled onto the study. The contribution of GG to the biopsy and Prostate Imaging Reporting and Data System (PI-RADS) score for PCa harboring adverse pathology were analyzed. Univariate and multivariate logistic regression analyses were performed to determine significant pathology predictors of adverse pathology for nomogram development. The nomogram was internally validated using bootstrapping with 1,000 iterations. The diagnostic performance of the nomogram was analyzed by receiver operating characteristics (ROC) analysis and decision curve analysis (DCA). A higher biopsy GG and PI-RADS score were associated with an increased likelihood of adverse pathology. Prostate specific antigen density (PSAD), biopsy GG, cribriform morphology on biopsy and PI-RADS score were significant predictors and were included in the nomogram. The ROC area under the curve of the nomogram was 0.88 (95% confidence interval, 0.84–0.91), with a high specificity (0.91) and moderate sensitivity (0.72). The novel nomogram was shown to have a higher net benefit for the prediction of adverse pathology in PCa, compared with any individual factors determined by DCA. Overall, a novel nomogram incorporating PSAD, PI-RADS score, biopsy GG and cribriform morphology on biopsy was shown to perform well in the prediction of PCa harboring adverse pathology at the time of radical prostatectomy. D.A. Spandidos 2020-09 2020-07-10 /pmc/articles/PMC7400272/ /pubmed/32782597 http://dx.doi.org/10.3892/ol.2020.11861 Text en Copyright: © Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Wang, Baojun
Gao, Jie
Zhang, Qing
Fu, Yao
Liu, Guangxiang
Zhang, Chengwei
Wei, Wang
Huang, Haifeng
Shi, Jiong
Li, Danyan
Guo, Hongqian
Diagnostic performance of a nomogram incorporating cribriform morphology for the prediction of adverse pathology in prostate cancer at radical prostatectomy
title Diagnostic performance of a nomogram incorporating cribriform morphology for the prediction of adverse pathology in prostate cancer at radical prostatectomy
title_full Diagnostic performance of a nomogram incorporating cribriform morphology for the prediction of adverse pathology in prostate cancer at radical prostatectomy
title_fullStr Diagnostic performance of a nomogram incorporating cribriform morphology for the prediction of adverse pathology in prostate cancer at radical prostatectomy
title_full_unstemmed Diagnostic performance of a nomogram incorporating cribriform morphology for the prediction of adverse pathology in prostate cancer at radical prostatectomy
title_short Diagnostic performance of a nomogram incorporating cribriform morphology for the prediction of adverse pathology in prostate cancer at radical prostatectomy
title_sort diagnostic performance of a nomogram incorporating cribriform morphology for the prediction of adverse pathology in prostate cancer at radical prostatectomy
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7400272/
https://www.ncbi.nlm.nih.gov/pubmed/32782597
http://dx.doi.org/10.3892/ol.2020.11861
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