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Combining prostate-specific antigen density with prostate imaging reporting and data system score version 2.1 to improve detection of clinically significant prostate cancer: A retrospective study

Globally, Prostate cancer (PCa) is the second most common cancer in the male population worldwide, but clinically significant prostate cancer (CSPCa) is more aggressive and causes to more deaths. The authors aimed to construct the risk category based on Prostate Imaging Reporting and Data System sco...

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Autores principales: Lei, Yin, Li, Tian Jie, Gu, Peng, Yang, Yu kun, Zhao, Lei, Gao, Chao, Hu, Juan, Liu, Xiao Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9539128/
https://www.ncbi.nlm.nih.gov/pubmed/36212411
http://dx.doi.org/10.3389/fonc.2022.992032
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author Lei, Yin
Li, Tian Jie
Gu, Peng
Yang, Yu kun
Zhao, Lei
Gao, Chao
Hu, Juan
Liu, Xiao Dong
author_facet Lei, Yin
Li, Tian Jie
Gu, Peng
Yang, Yu kun
Zhao, Lei
Gao, Chao
Hu, Juan
Liu, Xiao Dong
author_sort Lei, Yin
collection PubMed
description Globally, Prostate cancer (PCa) is the second most common cancer in the male population worldwide, but clinically significant prostate cancer (CSPCa) is more aggressive and causes to more deaths. The authors aimed to construct the risk category based on Prostate Imaging Reporting and Data System score version 2.1 (PI-RADS v2.1) in combination with Prostate-Specific Antigen Density (PSAD) to improve CSPCa detection and avoid unnecessary biopsy. Univariate and multivariate logistic regression and receiver-operating characteristic (ROC) curves were performed to compare the efficacy of the different predictors. The results revealed that PI-RADS v2.1 score and PSAD were independent predictors for CSPCa. Moreover, the combined factor shows a significantly higher predictive value than each single variable for the diagnosis of CSPCa. According to the risk stratification model constructed based on PI-RADS v2.1 score and PSAD, patients with PI-RADS v2.1 score of ≤2, or PI-RADS V2.1 score of 3 and PSA density of <0.15 ng/mL(2), can avoid unnecessary of prostate biopsy and does not miss clinically significant prostate cancer.
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spelling pubmed-95391282022-10-08 Combining prostate-specific antigen density with prostate imaging reporting and data system score version 2.1 to improve detection of clinically significant prostate cancer: A retrospective study Lei, Yin Li, Tian Jie Gu, Peng Yang, Yu kun Zhao, Lei Gao, Chao Hu, Juan Liu, Xiao Dong Front Oncol Oncology Globally, Prostate cancer (PCa) is the second most common cancer in the male population worldwide, but clinically significant prostate cancer (CSPCa) is more aggressive and causes to more deaths. The authors aimed to construct the risk category based on Prostate Imaging Reporting and Data System score version 2.1 (PI-RADS v2.1) in combination with Prostate-Specific Antigen Density (PSAD) to improve CSPCa detection and avoid unnecessary biopsy. Univariate and multivariate logistic regression and receiver-operating characteristic (ROC) curves were performed to compare the efficacy of the different predictors. The results revealed that PI-RADS v2.1 score and PSAD were independent predictors for CSPCa. Moreover, the combined factor shows a significantly higher predictive value than each single variable for the diagnosis of CSPCa. According to the risk stratification model constructed based on PI-RADS v2.1 score and PSAD, patients with PI-RADS v2.1 score of ≤2, or PI-RADS V2.1 score of 3 and PSA density of <0.15 ng/mL(2), can avoid unnecessary of prostate biopsy and does not miss clinically significant prostate cancer. Frontiers Media S.A. 2022-09-23 /pmc/articles/PMC9539128/ /pubmed/36212411 http://dx.doi.org/10.3389/fonc.2022.992032 Text en Copyright © 2022 Lei, Li, Gu, Yang, Zhao, Gao, Hu and Liu 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
Lei, Yin
Li, Tian Jie
Gu, Peng
Yang, Yu kun
Zhao, Lei
Gao, Chao
Hu, Juan
Liu, Xiao Dong
Combining prostate-specific antigen density with prostate imaging reporting and data system score version 2.1 to improve detection of clinically significant prostate cancer: A retrospective study
title Combining prostate-specific antigen density with prostate imaging reporting and data system score version 2.1 to improve detection of clinically significant prostate cancer: A retrospective study
title_full Combining prostate-specific antigen density with prostate imaging reporting and data system score version 2.1 to improve detection of clinically significant prostate cancer: A retrospective study
title_fullStr Combining prostate-specific antigen density with prostate imaging reporting and data system score version 2.1 to improve detection of clinically significant prostate cancer: A retrospective study
title_full_unstemmed Combining prostate-specific antigen density with prostate imaging reporting and data system score version 2.1 to improve detection of clinically significant prostate cancer: A retrospective study
title_short Combining prostate-specific antigen density with prostate imaging reporting and data system score version 2.1 to improve detection of clinically significant prostate cancer: A retrospective study
title_sort combining prostate-specific antigen density with prostate imaging reporting and data system score version 2.1 to improve detection of clinically significant prostate cancer: a retrospective study
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9539128/
https://www.ncbi.nlm.nih.gov/pubmed/36212411
http://dx.doi.org/10.3389/fonc.2022.992032
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