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The Barcelona Predictive Model of Clinically Significant Prostate Cancer
SIMPLE SUMMARY: Magnetic-resonance-imaging-based predictive models (MRI-PMs) improve the MRI prediction of clinically significant prostate cancer (csPCa) in prostate biopsies. Risk calculators (RC) provide easy individual assessment of csPCa likelihood. MRI-PMs have been analysed in overall populati...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8946272/ https://www.ncbi.nlm.nih.gov/pubmed/35326740 http://dx.doi.org/10.3390/cancers14061589 |
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author | Morote, Juan Borque-Fernando, Angel Triquell, Marina Celma, Anna Regis, Lucas Escobar, Manel Mast, Richard de Torres, Inés M. Semidey, María E. Abascal, José M. Sola, Carles Servian, Pol Salvador, Daniel Santamaría, Anna Planas, Jacques Esteban, Luis M. Trilla, Enrique |
author_facet | Morote, Juan Borque-Fernando, Angel Triquell, Marina Celma, Anna Regis, Lucas Escobar, Manel Mast, Richard de Torres, Inés M. Semidey, María E. Abascal, José M. Sola, Carles Servian, Pol Salvador, Daniel Santamaría, Anna Planas, Jacques Esteban, Luis M. Trilla, Enrique |
author_sort | Morote, Juan |
collection | PubMed |
description | SIMPLE SUMMARY: Magnetic-resonance-imaging-based predictive models (MRI-PMs) improve the MRI prediction of clinically significant prostate cancer (csPCa) in prostate biopsies. Risk calculators (RC) provide easy individual assessment of csPCa likelihood. MRI-PMs have been analysed in overall populations of men suspected to have PCa, but they have never been analysed according to the prostate imaging-report and data system (PI-RADS) categories. Therefore, the true clinical usefulness of MRI-PMs regarding the specific PI-RADS categories is unknown. ABSTRACT: A new and externally validated MRI-PM for csPCa was developed in the metropolitan area of Barcelona, and a web-RC designed with the new option of selecting the csPCa probability threshold. The development cohort comprised 1486 men scheduled to undergo a 3-tesla multiparametric MRI (mpMRI) and guided and/or systematic biopsies in one academic institution of Barcelona. The external validation cohort comprised 946 men in whom the same diagnostic approach was carried out as in the development cohort, in two other academic institutions of the same metropolitan area. CsPCa was detected in 36.9% of men in the development cohort and 40.8% in the external validation cohort (p = 0.054). The area under the curve of mpMRI increased from 0.842 to 0.897 in the developed MRI-PM (p < 0.001), and from 0.743 to 0.858 in the external validation cohort (p < 0.001). A selected 15% threshold avoided 40.1% of prostate biopsies and missed 5.4% of the 36.9% csPCa detected in the development cohort. In men with PI-RADS <3, 4.3% would be biopsied and 32.3% of all existing 4.2% of csPCa would be detected. In men with PI-RADS 3, 62% of prostate biopsies would be avoided and 28% of all existing 12.4% of csPCa would be undetected. In men with PI-RADS 4, 4% of prostate biopsies would be avoided and 0.6% of all existing 43.1% of csPCa would be undetected. In men with PI-RADS 5, 0.6% of prostate biopsies would be avoided and none of the existing 42.0% of csPCa would be undetected. The Barcelona MRI-PM presented good performance on the overall population; however, its clinical usefulness varied regarding the PI-RADS category. The selection of csPCa probability thresholds in the designed RC may facilitate external validation and outperformance of MRI-PMs in specific PI-RADS categories. |
format | Online Article Text |
id | pubmed-8946272 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-89462722022-03-25 The Barcelona Predictive Model of Clinically Significant Prostate Cancer Morote, Juan Borque-Fernando, Angel Triquell, Marina Celma, Anna Regis, Lucas Escobar, Manel Mast, Richard de Torres, Inés M. Semidey, María E. Abascal, José M. Sola, Carles Servian, Pol Salvador, Daniel Santamaría, Anna Planas, Jacques Esteban, Luis M. Trilla, Enrique Cancers (Basel) Article SIMPLE SUMMARY: Magnetic-resonance-imaging-based predictive models (MRI-PMs) improve the MRI prediction of clinically significant prostate cancer (csPCa) in prostate biopsies. Risk calculators (RC) provide easy individual assessment of csPCa likelihood. MRI-PMs have been analysed in overall populations of men suspected to have PCa, but they have never been analysed according to the prostate imaging-report and data system (PI-RADS) categories. Therefore, the true clinical usefulness of MRI-PMs regarding the specific PI-RADS categories is unknown. ABSTRACT: A new and externally validated MRI-PM for csPCa was developed in the metropolitan area of Barcelona, and a web-RC designed with the new option of selecting the csPCa probability threshold. The development cohort comprised 1486 men scheduled to undergo a 3-tesla multiparametric MRI (mpMRI) and guided and/or systematic biopsies in one academic institution of Barcelona. The external validation cohort comprised 946 men in whom the same diagnostic approach was carried out as in the development cohort, in two other academic institutions of the same metropolitan area. CsPCa was detected in 36.9% of men in the development cohort and 40.8% in the external validation cohort (p = 0.054). The area under the curve of mpMRI increased from 0.842 to 0.897 in the developed MRI-PM (p < 0.001), and from 0.743 to 0.858 in the external validation cohort (p < 0.001). A selected 15% threshold avoided 40.1% of prostate biopsies and missed 5.4% of the 36.9% csPCa detected in the development cohort. In men with PI-RADS <3, 4.3% would be biopsied and 32.3% of all existing 4.2% of csPCa would be detected. In men with PI-RADS 3, 62% of prostate biopsies would be avoided and 28% of all existing 12.4% of csPCa would be undetected. In men with PI-RADS 4, 4% of prostate biopsies would be avoided and 0.6% of all existing 43.1% of csPCa would be undetected. In men with PI-RADS 5, 0.6% of prostate biopsies would be avoided and none of the existing 42.0% of csPCa would be undetected. The Barcelona MRI-PM presented good performance on the overall population; however, its clinical usefulness varied regarding the PI-RADS category. The selection of csPCa probability thresholds in the designed RC may facilitate external validation and outperformance of MRI-PMs in specific PI-RADS categories. MDPI 2022-03-21 /pmc/articles/PMC8946272/ /pubmed/35326740 http://dx.doi.org/10.3390/cancers14061589 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Morote, Juan Borque-Fernando, Angel Triquell, Marina Celma, Anna Regis, Lucas Escobar, Manel Mast, Richard de Torres, Inés M. Semidey, María E. Abascal, José M. Sola, Carles Servian, Pol Salvador, Daniel Santamaría, Anna Planas, Jacques Esteban, Luis M. Trilla, Enrique The Barcelona Predictive Model of Clinically Significant Prostate Cancer |
title | The Barcelona Predictive Model of Clinically Significant Prostate Cancer |
title_full | The Barcelona Predictive Model of Clinically Significant Prostate Cancer |
title_fullStr | The Barcelona Predictive Model of Clinically Significant Prostate Cancer |
title_full_unstemmed | The Barcelona Predictive Model of Clinically Significant Prostate Cancer |
title_short | The Barcelona Predictive Model of Clinically Significant Prostate Cancer |
title_sort | barcelona predictive model of clinically significant prostate cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8946272/ https://www.ncbi.nlm.nih.gov/pubmed/35326740 http://dx.doi.org/10.3390/cancers14061589 |
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