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Using clinical parameters to predict prostate cancer and reduce the unnecessary biopsy among patients with PSA in the gray zone
The gold standard for prostate cancer (PCa) diagnosis is prostate biopsy. However, it remines controversial as an invasive mean for patients with PSA levels in the gray zone (4–10 ng/mL). This study aimed to develop strategy to reduce the unnecessary prostate biopsy. We retrospectively identified 23...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083895/ https://www.ncbi.nlm.nih.gov/pubmed/32198373 http://dx.doi.org/10.1038/s41598-020-62015-w |
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author | Liu, Junxiao Dong, Biao Qu, Wugong Wang, Jiange Xu, Yue Yu, Shuanbao Zhang, Xuepei |
author_facet | Liu, Junxiao Dong, Biao Qu, Wugong Wang, Jiange Xu, Yue Yu, Shuanbao Zhang, Xuepei |
author_sort | Liu, Junxiao |
collection | PubMed |
description | The gold standard for prostate cancer (PCa) diagnosis is prostate biopsy. However, it remines controversial as an invasive mean for patients with PSA levels in the gray zone (4–10 ng/mL). This study aimed to develop strategy to reduce the unnecessary prostate biopsy. We retrospectively identified 235 patients with serum total PSA testing in the gray zone before prostate biopsy between 2014 and 2018. Age, PSA derivates, prostate volume and multiparametric magnetic imaging (mpMRI) examination were assessed as predictors for PCa and clinically significant PCa with Gleason score ≥ 7 (CSPCa). Univariate analysis showed that prostate volume, PSAD, and mpMRI examination were significant predictors of PCa and CSPCa (P < 0.05). The differences of diagnostic accuracy between mpMRI examination (AUC = 0.69) and other clinical parameters in diagnostic accuracy for PCa were not statistically significant. However, mpMRI examination (AUC = 0.79) outperformed prostate volume and PSAD in diagnosis of CSPCa. The multivariate models (AUC = 0.79 and 0.84 for PCa and CSPCa) performed significantly better than mpMRI examination for detection of PCa (P = 0.003) and CSPCa (P = 0.036) among patients with PSA level in the gray zone. At the same level of sensitivity as the mpMRI examination to diagnose PCa, applying the multivariate models could reduce the number of biopsies by 5% compared with mpMRI examination. Overall, our results supported the view that the multivariate model could reduce unnecessary biopsies without compromising the ability to diagnose PCa and CSPCa. Further prospective validation is required. |
format | Online Article Text |
id | pubmed-7083895 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70838952020-03-26 Using clinical parameters to predict prostate cancer and reduce the unnecessary biopsy among patients with PSA in the gray zone Liu, Junxiao Dong, Biao Qu, Wugong Wang, Jiange Xu, Yue Yu, Shuanbao Zhang, Xuepei Sci Rep Article The gold standard for prostate cancer (PCa) diagnosis is prostate biopsy. However, it remines controversial as an invasive mean for patients with PSA levels in the gray zone (4–10 ng/mL). This study aimed to develop strategy to reduce the unnecessary prostate biopsy. We retrospectively identified 235 patients with serum total PSA testing in the gray zone before prostate biopsy between 2014 and 2018. Age, PSA derivates, prostate volume and multiparametric magnetic imaging (mpMRI) examination were assessed as predictors for PCa and clinically significant PCa with Gleason score ≥ 7 (CSPCa). Univariate analysis showed that prostate volume, PSAD, and mpMRI examination were significant predictors of PCa and CSPCa (P < 0.05). The differences of diagnostic accuracy between mpMRI examination (AUC = 0.69) and other clinical parameters in diagnostic accuracy for PCa were not statistically significant. However, mpMRI examination (AUC = 0.79) outperformed prostate volume and PSAD in diagnosis of CSPCa. The multivariate models (AUC = 0.79 and 0.84 for PCa and CSPCa) performed significantly better than mpMRI examination for detection of PCa (P = 0.003) and CSPCa (P = 0.036) among patients with PSA level in the gray zone. At the same level of sensitivity as the mpMRI examination to diagnose PCa, applying the multivariate models could reduce the number of biopsies by 5% compared with mpMRI examination. Overall, our results supported the view that the multivariate model could reduce unnecessary biopsies without compromising the ability to diagnose PCa and CSPCa. Further prospective validation is required. Nature Publishing Group UK 2020-03-20 /pmc/articles/PMC7083895/ /pubmed/32198373 http://dx.doi.org/10.1038/s41598-020-62015-w Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Liu, Junxiao Dong, Biao Qu, Wugong Wang, Jiange Xu, Yue Yu, Shuanbao Zhang, Xuepei Using clinical parameters to predict prostate cancer and reduce the unnecessary biopsy among patients with PSA in the gray zone |
title | Using clinical parameters to predict prostate cancer and reduce the unnecessary biopsy among patients with PSA in the gray zone |
title_full | Using clinical parameters to predict prostate cancer and reduce the unnecessary biopsy among patients with PSA in the gray zone |
title_fullStr | Using clinical parameters to predict prostate cancer and reduce the unnecessary biopsy among patients with PSA in the gray zone |
title_full_unstemmed | Using clinical parameters to predict prostate cancer and reduce the unnecessary biopsy among patients with PSA in the gray zone |
title_short | Using clinical parameters to predict prostate cancer and reduce the unnecessary biopsy among patients with PSA in the gray zone |
title_sort | using clinical parameters to predict prostate cancer and reduce the unnecessary biopsy among patients with psa in the gray zone |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083895/ https://www.ncbi.nlm.nih.gov/pubmed/32198373 http://dx.doi.org/10.1038/s41598-020-62015-w |
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