A clinically significant prostate cancer predictive model using digital rectal examination prostate volume category to stratify initial prostate cancer suspicion and reduce magnetic resonance imaging demand

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• dc.contributor.author Morote, Juan
• dc.contributor.author Borque-Fernando, Ángel
• dc.contributor.author Triquell, Marina
• dc.contributor.author Campistol, Miriam
• dc.contributor.author Celma, Anna
• dc.contributor.author Regis, Lucas
• dc.contributor.author Abascal-Junquera, José María
• dc.contributor.author Servian, Pol
• dc.contributor.author Planas, Jacques
• dc.contributor.author Mendez Fernández, Olga
• dc.contributor.author Esteban, Luis M.
• dc.contributor.author Trilla, Enrique
• dc.date.accessioned 2023-03-01T07:29:29Z
• dc.date.available 2023-03-01T07:29:29Z
• dc.date.issued 2022
• dc.description.abstract A predictive model including age, PCa family history, biopsy status (initial vs repeat), DRE (normal vs abnormal), serum prostate-specific antigen (PSA), and DRE prostate volume ca-tegory was developed to stratify initial PCa suspicion in 1486 men with PSA > 3 ng/mL and/or abnormal DRE, in whom mpMRI followed; 2- to 4-core TRUS-guided biopsies where Prostate Imaging Report and Data System (PI-RADS) > 3 lesions and/or 12-core TRUS systematic biopsies were performed in one academic institution between 1 January 2016-31 December 2019. The csPCa detection rate, defined as International Society of Uro-Pathology grade group 2 or higher, was 36.9%. An external validation of designed BCN-RC 1 was carried out on 946 men from two other institutions in the same metropolitan area, using the same criteria of PCa suspicion and diagnostic approach, yielded a csPCa detection rate of 40.8%. The areas under the receiver operating characteristic curves of BCN-RC 1 were 0.823 (95% CI: 0.800-0.846) in the development cohort and 0.837 (95% CI: 0.811-0.863) in the validation cohort (p = 0.447). In both cohorts, BCN-RC 1 exhibited net benefit over performing mpMRI in all men from 8 and 12% risk thresholds, respectively. At 0.95 sensitivity of csPCa, the specificities of BCN-RC 1 were 0.24 (95% CI: 0.22-0.26) in the development cohort and 0.34 (95% CI: 0.31-0.37) in the validation cohort (p < 0.001). The percentages of avoided mpMRI scans were 17.2% in the development cohort and 22.3% in the validation cohort, missing between 1.8% and 2% of csPCa among men at risk of PCa. In summary, BCN-RC 1 can stratify initial PCa suspicion, reducing the demand of mpMRI, with an acceptable loss of csPCa.
• dc.format.mimetype application/pdf
• dc.identifier.citation Morote J, Borque-Fernando Á, Triquell M, Campistol M, Celma A, Regis L, et al. A clinically significant prostate cancer predictive model using digital rectal examination prostate volume category to stratify initial prostate cancer suspicion and reduce magnetic resonance imaging demand. Cancers (Basel). 2022 Oct 18; 14(20): 5100. DOI: 10.3390/cancers14205100
• dc.identifier.doi http://dx.doi.org/10.3390/cancers14205100
• dc.identifier.issn 2072-6694
• dc.identifier.uri http://hdl.handle.net/10230/55983
• dc.language.iso eng
• dc.publisher MDPI
• dc.rights Copyright © 2022 by Morote J, Borque-Fernando Á, Triquell M, Campistol M, Celma A, Regis L, et al. 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 (http://creativecommons.org/licenses/by/4.0/).
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Clinically significant
• dc.subject.keyword Development
• dc.subject.keyword External validation
• dc.subject.keyword Magnetic resonance imaging
• dc.subject.keyword Predictive model
• dc.subject.keyword Prostate cancer
• dc.subject.keyword Risk calculator
• dc.subject.keyword Suspicion
• dc.title A clinically significant prostate cancer predictive model using digital rectal examination prostate volume category to stratify initial prostate cancer suspicion and reduce magnetic resonance imaging demand
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion