The Barcelona Predictive Model of Clinically Significant Prostate Cancer

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 suspe...

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Autores: Morote Robles, Juan|||0000-0002-2168-323X, Borque-Fernando, Ángel|||0000-0003-0178-4567, Triquell, Marina|||0000-0003-3881-8177, Celma, Ana|||0000-0002-3128-3811, Regis, Lucas|||0000-0001-7121-1946, Escobar, Manuel|||0000-0002-3794-2224, Mast, Richard|||0000-0001-6005-800X, de Torres, Inés|||0000-0002-5495-9140, Semidey Raven, Maria Eugenia|||0000-0001-8539-9265, Abascal, Jose Maria|||0000-0001-8374-6593, Solà Belda, Carles|||0000-0002-2646-0465, Servian, Pol|||0000-0002-3727-8159, Salvador Hidalgo, Daniel, Santamaría Margalef, Anna|||0000-0001-6726-8990, Planas Morin, Jacques|||0000-0002-0222-584X, Esteban, Luis M.|||0000-0002-3007-302X, Trilla Herrera, Enrique|||0000-0001-9401-0872
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:258179
Acceso en línea:https://ddd.uab.cat/record/258179
https://dx.doi.org/urn:doi:10.3390/cancers14061589
Access Level:acceso abierto
Palabra clave:Clinically significant prostate cancer
Magnetic resonance imaging
Predictive model
Risk calculator
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spelling The Barcelona Predictive Model of Clinically Significant Prostate CancerMorote Robles, Juan|||0000-0002-2168-323XBorque-Fernando, Ángel|||0000-0003-0178-4567Triquell, Marina|||0000-0003-3881-8177Celma, Ana|||0000-0002-3128-3811Regis, Lucas|||0000-0001-7121-1946Escobar, Manuel|||0000-0002-3794-2224Mast, Richard|||0000-0001-6005-800Xde Torres, Inés|||0000-0002-5495-9140Semidey Raven, Maria Eugenia|||0000-0001-8539-9265Abascal, Jose Maria|||0000-0001-8374-6593Solà Belda, Carles|||0000-0002-2646-0465Servian, Pol|||0000-0002-3727-8159Salvador Hidalgo, DanielSantamaría Margalef, Anna|||0000-0001-6726-8990Planas Morin, Jacques|||0000-0002-0222-584XEsteban, Luis M.|||0000-0002-3007-302XTrilla Herrera, Enrique|||0000-0001-9401-0872Clinically significant prostate cancerMagnetic resonance imagingPredictive modelRisk calculatorMagnetic-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. 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. 22022-01-0120222022-01-01Articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://ddd.uab.cat/record/258179https://dx.doi.org/urn:doi:10.3390/cancers14061589reponame:Dipòsit Digital de Documents de la UABinstname:Universitat Autònoma de BarcelonaInglésengInstituto de Salud Carlos III https://doi.org/10.13039/501100004587 PI20/01666open accesshttp://purl.org/coar/access_right/c_abf2Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:ddd.uab.cat:2581792026-06-06T12:50:31Z
dc.title.none.fl_str_mv The Barcelona Predictive Model of Clinically Significant Prostate Cancer
title The Barcelona Predictive Model of Clinically Significant Prostate Cancer
spellingShingle The Barcelona Predictive Model of Clinically Significant Prostate Cancer
Morote Robles, Juan|||0000-0002-2168-323X
Clinically significant prostate cancer
Magnetic resonance imaging
Predictive model
Risk calculator
title_short 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_sort The Barcelona Predictive Model of Clinically Significant Prostate Cancer
dc.creator.none.fl_str_mv Morote Robles, Juan|||0000-0002-2168-323X
Borque-Fernando, Ángel|||0000-0003-0178-4567
Triquell, Marina|||0000-0003-3881-8177
Celma, Ana|||0000-0002-3128-3811
Regis, Lucas|||0000-0001-7121-1946
Escobar, Manuel|||0000-0002-3794-2224
Mast, Richard|||0000-0001-6005-800X
de Torres, Inés|||0000-0002-5495-9140
Semidey Raven, Maria Eugenia|||0000-0001-8539-9265
Abascal, Jose Maria|||0000-0001-8374-6593
Solà Belda, Carles|||0000-0002-2646-0465
Servian, Pol|||0000-0002-3727-8159
Salvador Hidalgo, Daniel
Santamaría Margalef, Anna|||0000-0001-6726-8990
Planas Morin, Jacques|||0000-0002-0222-584X
Esteban, Luis M.|||0000-0002-3007-302X
Trilla Herrera, Enrique|||0000-0001-9401-0872
author Morote Robles, Juan|||0000-0002-2168-323X
author_facet Morote Robles, Juan|||0000-0002-2168-323X
Borque-Fernando, Ángel|||0000-0003-0178-4567
Triquell, Marina|||0000-0003-3881-8177
Celma, Ana|||0000-0002-3128-3811
Regis, Lucas|||0000-0001-7121-1946
Escobar, Manuel|||0000-0002-3794-2224
Mast, Richard|||0000-0001-6005-800X
de Torres, Inés|||0000-0002-5495-9140
Semidey Raven, Maria Eugenia|||0000-0001-8539-9265
Abascal, Jose Maria|||0000-0001-8374-6593
Solà Belda, Carles|||0000-0002-2646-0465
Servian, Pol|||0000-0002-3727-8159
Salvador Hidalgo, Daniel
Santamaría Margalef, Anna|||0000-0001-6726-8990
Planas Morin, Jacques|||0000-0002-0222-584X
Esteban, Luis M.|||0000-0002-3007-302X
Trilla Herrera, Enrique|||0000-0001-9401-0872
author_role author
author2 Borque-Fernando, Ángel|||0000-0003-0178-4567
Triquell, Marina|||0000-0003-3881-8177
Celma, Ana|||0000-0002-3128-3811
Regis, Lucas|||0000-0001-7121-1946
Escobar, Manuel|||0000-0002-3794-2224
Mast, Richard|||0000-0001-6005-800X
de Torres, Inés|||0000-0002-5495-9140
Semidey Raven, Maria Eugenia|||0000-0001-8539-9265
Abascal, Jose Maria|||0000-0001-8374-6593
Solà Belda, Carles|||0000-0002-2646-0465
Servian, Pol|||0000-0002-3727-8159
Salvador Hidalgo, Daniel
Santamaría Margalef, Anna|||0000-0001-6726-8990
Planas Morin, Jacques|||0000-0002-0222-584X
Esteban, Luis M.|||0000-0002-3007-302X
Trilla Herrera, Enrique|||0000-0001-9401-0872
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Clinically significant prostate cancer
Magnetic resonance imaging
Predictive model
Risk calculator
topic Clinically significant prostate cancer
Magnetic resonance imaging
Predictive model
Risk calculator
description 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. 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.
publishDate 2022
dc.date.none.fl_str_mv 2
2022-01-01
2022
2022-01-01
dc.type.none.fl_str_mv Article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.none.fl_str_mv https://ddd.uab.cat/record/258179
https://dx.doi.org/urn:doi:10.3390/cancers14061589
url https://ddd.uab.cat/record/258179
https://dx.doi.org/urn:doi:10.3390/cancers14061589
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Instituto de Salud Carlos III https://doi.org/10.13039/501100004587 PI20/01666
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Dipòsit Digital de Documents de la UAB
instname:Universitat Autònoma de Barcelona
instname_str Universitat Autònoma de Barcelona
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