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Prediction of extracapsular extension in prostate cancer using the Likert scale combined with clinical and pathological parameters
ABSTRACT: This study aimed to investigate the independent clinical, pathological, and radiological factors associated with extracapsular extension in radical prostatectomy specimens and to improve the accuracy of predicting extracapsular extension of prostate cancer before surgery. METHODS: From Aug...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442837/ https://www.ncbi.nlm.nih.gov/pubmed/37614509 http://dx.doi.org/10.3389/fonc.2023.1229552 |
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author | Wang, Jun-guang Huang, Bin-tian Huang, Li Zhang, Xia He, Pei-pei Chen, Jun-bo |
author_facet | Wang, Jun-guang Huang, Bin-tian Huang, Li Zhang, Xia He, Pei-pei Chen, Jun-bo |
author_sort | Wang, Jun-guang |
collection | PubMed |
description | ABSTRACT: This study aimed to investigate the independent clinical, pathological, and radiological factors associated with extracapsular extension in radical prostatectomy specimens and to improve the accuracy of predicting extracapsular extension of prostate cancer before surgery. METHODS: From August 2018 to June 2023, the clinical and pathological data of 229 patients with confirmed prostate cancer underwent radical prostatectomy from The Second Hospital of Yinzhou. The patients’ multiparametric magnetic resonance imaging data were graded using the Likert scale. The chi-square or independent-sample T-test was used to analyze the related factors for an extracapsular extension. Multivariate analysis was used to identify independent factors associated with extracapsular extension in prostate cancer. Additionally, receiver operating characteristic curve analysis was used to calculate the area under the curve and assess the diagnostic performance of our model. The clinical decision curve was used to analyze the clinical net income of Likert scale, biopsy positive rate, biopsy GG, and combined mode. RESULTS: Of the 229 patients, 52 had an extracapsular extension, and 177 did not. Multivariate analysis showed that the Likert scale score, biopsy grade group and biopsy positive rate were independent risk factors for extracapsular extension in prostate cancer. The area under the curves for the Likert scale score, biopsy grade group, and biopsy positive rate were 0.802, 0.762, and 0.796, respectively. Furthermore, there was no significant difference in the diagnostic efficiency for extracapsular extension (P>0.05). However, when these three factors were combined, the diagnostic efficiency was significantly improved, and the area under the curve increased to 0.905 (P<0.05). In the analysis of the decision curve, The clinical net income of the combined model is obviously higher than that of Likert scale, biopsy positive rate, and biopsy GG. CONCLUSION: The Likert scale, biopsy grade group and biopsy positive rate are independent risk factors for extracapsular extension in prostate cancer, and their combination can significantly improve the diagnostic efficiency for an extracapsular extension. |
format | Online Article Text |
id | pubmed-10442837 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104428372023-08-23 Prediction of extracapsular extension in prostate cancer using the Likert scale combined with clinical and pathological parameters Wang, Jun-guang Huang, Bin-tian Huang, Li Zhang, Xia He, Pei-pei Chen, Jun-bo Front Oncol Oncology ABSTRACT: This study aimed to investigate the independent clinical, pathological, and radiological factors associated with extracapsular extension in radical prostatectomy specimens and to improve the accuracy of predicting extracapsular extension of prostate cancer before surgery. METHODS: From August 2018 to June 2023, the clinical and pathological data of 229 patients with confirmed prostate cancer underwent radical prostatectomy from The Second Hospital of Yinzhou. The patients’ multiparametric magnetic resonance imaging data were graded using the Likert scale. The chi-square or independent-sample T-test was used to analyze the related factors for an extracapsular extension. Multivariate analysis was used to identify independent factors associated with extracapsular extension in prostate cancer. Additionally, receiver operating characteristic curve analysis was used to calculate the area under the curve and assess the diagnostic performance of our model. The clinical decision curve was used to analyze the clinical net income of Likert scale, biopsy positive rate, biopsy GG, and combined mode. RESULTS: Of the 229 patients, 52 had an extracapsular extension, and 177 did not. Multivariate analysis showed that the Likert scale score, biopsy grade group and biopsy positive rate were independent risk factors for extracapsular extension in prostate cancer. The area under the curves for the Likert scale score, biopsy grade group, and biopsy positive rate were 0.802, 0.762, and 0.796, respectively. Furthermore, there was no significant difference in the diagnostic efficiency for extracapsular extension (P>0.05). However, when these three factors were combined, the diagnostic efficiency was significantly improved, and the area under the curve increased to 0.905 (P<0.05). In the analysis of the decision curve, The clinical net income of the combined model is obviously higher than that of Likert scale, biopsy positive rate, and biopsy GG. CONCLUSION: The Likert scale, biopsy grade group and biopsy positive rate are independent risk factors for extracapsular extension in prostate cancer, and their combination can significantly improve the diagnostic efficiency for an extracapsular extension. Frontiers Media S.A. 2023-08-08 /pmc/articles/PMC10442837/ /pubmed/37614509 http://dx.doi.org/10.3389/fonc.2023.1229552 Text en Copyright © 2023 Wang, Huang, Huang, Zhang, He and Chen https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Wang, Jun-guang Huang, Bin-tian Huang, Li Zhang, Xia He, Pei-pei Chen, Jun-bo Prediction of extracapsular extension in prostate cancer using the Likert scale combined with clinical and pathological parameters |
title | Prediction of extracapsular extension in prostate cancer using the Likert scale combined with clinical and pathological parameters |
title_full | Prediction of extracapsular extension in prostate cancer using the Likert scale combined with clinical and pathological parameters |
title_fullStr | Prediction of extracapsular extension in prostate cancer using the Likert scale combined with clinical and pathological parameters |
title_full_unstemmed | Prediction of extracapsular extension in prostate cancer using the Likert scale combined with clinical and pathological parameters |
title_short | Prediction of extracapsular extension in prostate cancer using the Likert scale combined with clinical and pathological parameters |
title_sort | prediction of extracapsular extension in prostate cancer using the likert scale combined with clinical and pathological parameters |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442837/ https://www.ncbi.nlm.nih.gov/pubmed/37614509 http://dx.doi.org/10.3389/fonc.2023.1229552 |
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