The Barcelona Predictive Model of Clinically Significant Prostate Cancer
Morote Robles, Juan (Universitat Autònoma de Barcelona. Departament de Cirurgia)
Borque-Fernando, Ángel (Hospital Universitario Miguel Servet (Saragossa))
Triquell, Marina (Universitat Autònoma de Barcelona. Departament de Cirurgia)
Celma, Ana (Universitat Autònoma de Barcelona. Departament de Cirurgia)
Regis, Lucas (Universitat Autònoma de Barcelona. Departament de Cirurgia)
Escobar, Manel (Hospital Universitari Vall d'Hebron)
Mast, Richard (Hospital Universitari Vall d'Hebron. Institut de Recerca)
de Torres, Inés (Universitat Autònoma de Barcelona. Departament de Ciències Morfològiques)
Semidey, María E. (Universitat Autònoma de Barcelona. Departament de Ciències Morfològiques)
Abascal, Jose Maria (Parc de Salut MAR de Barcelona)
Solà Belda, Carles (Parc de Salut MAR de Barcelona)
Servian, Pol (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol)
Salvador Hidalgo, Daniel (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol)
Santamaría, Anna (Hospital Universitari Vall d'Hebron. Institut de Recerca)
Planas, Jacques (Hospital Universitari Vall d'Hebron)
Esteban, Luis M. (Universidad de Zaragoza. Departamento de Matemática Aplicada)
Trilla Herrera, Enrique (Universitat Autònoma de Barcelona. Departament de Cirurgia)

Data:	2022
Resum:	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.
Ajuts:	Instituto de Salud Carlos III PI20/01666
Drets:	Aquest 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.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Clinically significant prostate cancer ; Magnetic resonance imaging ; Predictive model ; Risk calculator
Publicat a:	Cancers, Vol. 14 (march 2022) , ISSN 2072-6694

DOI: 10.3390/cancers14061589
PMID: 35326740

13 p, 1.7 MB

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Documents de recerca > Documents dels grups de recerca de la UAB > Centres i grups de recerca (producció científica) > Ciències de la salut i biociències > Institut d'Investigació en Ciencies de la Salut Germans Trias i Pujol (IGTP)
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