Short communication (Scientific journals)
European validation of the Barcelona magnetic resonance predictive model for significant prostate cancer detection in prostate biopsies.
Morote, Juan; Miró, Berta; Regis, Lucas et al.
2026In BJUI compass, 7 (4), p. 70198
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Keywords :
early detection; federated network; predictive models; significant prostate cancer; validation; Surgery; Oncology; Nephrology; Urology
Abstract :
[en] Early detection of significant prostate cancer (sPCa) has notably improved with the widespread use of magnetic resonance imaging (MRI) and targeted biopsies. This advancement has contributed to the recommendation for PCa screening in the European Union. Nevertheless, PCa suspicion is still primarily based on a serum prostate-specific antigen (PSA) level greater than 3.0 ng/mL and/or a suspicious digital rectal examination (DRE). Prostate MRI is then requested to identify lesions suspected of harbouring sPCa, particularly when the Prostate Imaging-Reporting and Data System (PI-RADS) score is above 2. In such cases, both targeted biopsies of suspicious lesions and systematic biopsies are recommended, whereas prostate biopsy is typically avoided when the PI-RADS score is below 3. The European Association of Urology recommends the use of predictive models to reduce unnecessary prostate biopsies and the over-detection of insignificant prostate cancer (iPCa), especially in uncertain scenarios as PI-RADS 3 where the mean rate of sPCa detection is 20% and the overdetection of iPCa remains up to 50%.1 Accessible web- or smartphone-based risk calculators are essential for integrating predictive models into routine practice for assessing individual sPCa likelihood. Furthermore, validating these predictive models in populations different from those used in their development is crucial to ensure generalizability and clinical reliability.
Disciplines :
Urology & nephrology
Author, co-author :
Morote, Juan ;  Department of Surgery Universitat Autònoma de Barcelona Bellaterra Spain ; Department of Urology Vall d'Hebron University Hospital Barcelona Spain ; Research Group of Urology Vall d'Hebron Research Institute Barcelona Spain
Miró, Berta ;  Statistics Unit Vall d'Hebron Research Institute Barcelona Spain
Regis, Lucas ;  Department of Urology Vall d'Hebron University Hospital Barcelona Spain ; Research Group of Urology Vall d'Hebron Research Institute Barcelona Spain
Cousin, François  ;  Université de Liège - ULiège > Département des sciences cliniques
Duflot, Patrick  ;  Centre Hospitalier Universitaire de Liège - CHU > > Secteur Projets Recherche eHealth et Système d'information (PReHSI)
Kolh, Philippe  ;  Université de Liège - ULiège > Département des sciences biomédicales et précliniques > Biochimie et physiologie générales, humaines et pathologiques
Andalò, Alice ;  Data Unit IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori" Meldola Italy
Gentili, Nicola;  Data Unit IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori" Meldola Italy
Merloni, Filippo ;  Data Unit IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori" Meldola Italy
Iamurri, Andrea Prochowski ;  Medical Oncology Unit IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori" Meldola Italy
Ferroni, Fabio ;  Radiology Unit IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori" Meldola Italy
Trilla, Enrique ;  Department of Surgery Universitat Autònoma de Barcelona Bellaterra Spain ; Department of Urology Vall d'Hebron University Hospital Barcelona Spain ; Research Group of Urology Vall d'Hebron Research Institute Barcelona Spain
Méndez, Olga;  Research Group of Urology Vall d'Hebron Research Institute Barcelona Spain
More authors (3 more) Less
Language :
English
Title :
European validation of the Barcelona magnetic resonance predictive model for significant prostate cancer detection in prostate biopsies.
Alternative titles :
[en] Not Available.
Publication date :
April 2026
Journal title :
BJUI compass
eISSN :
2688-4526
Publisher :
John Wiley and Sons Inc, United States
Volume :
7
Issue :
4
Pages :
e70198
Peer reviewed :
Peer Reviewed verified by ORBi
European Projects :
HE - 101095382 - FLUTE - Federate Learning and mUlti-party computation Techniques for prostatE cancer
Name of the research project :
Federated Learning and mUlti-party computation Techniques for prostatE cancer (FLUTE)
Funders :
EU - European Union
Funding number :
101095382
Funding text :
This study was funded by the FLUTE project HORIZON-HLTH-2022-IND-13 action under the Horizon Europe Framework with grant agreement no. 101095382.
Available on ORBi :
since 12 June 2026

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