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. 2025 Mar;28(1):173-179.
doi: 10.1038/s41391-024-00872-6. Epub 2024 Jul 24.

Refining clinically relevant cut-offs of prostate specific antigen density for risk stratification in patients with PI-RADS 3 lesions

Georges Mjaess #  1 , Laura Haddad #  1 , Teddy Jabbour  1 , Arthur Baudewyns  1 , Henri-Alexandre Bourgeno  1 , Yolène Lefebvre  2 , Mariaconsiglia Ferriero  3 , Giuseppe Simone  3 , Alexandre Fourcade  4 , Georges Fournier  4 , Marco Oderda  5 , Paolo Gontero  5 , Adrian Bernal-Gomez  6 , Alessandro Mastrorosa  6 , Jean-Baptiste Roche  6 , Rawad Abou Zahr  7 , Guillaume Ploussard  7 , Gaelle Fiard  8 , Adam Halinski  9 , Katerina Rysankova  10   11 , Charles Dariane  12 , Gina Delavar  13 , Julien Anract  13 , Nicolas Barry Delongchamps  13 , Alexandre Patrick Bui  14 , Fayek Taha  14 , Olivier Windisch  15 , Daniel Benamran  15 , Gregoire Assenmacher  16 , Jan Benijts  16 , Karsten Guenzel  17 , Thierry Roumeguère  1 , Alexandre Peltier  1 , Romain Diamand  18
Affiliations

Refining clinically relevant cut-offs of prostate specific antigen density for risk stratification in patients with PI-RADS 3 lesions

Georges Mjaess et al. Prostate Cancer Prostatic Dis. 2025 Mar.

Abstract

Background: Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions, identified through multiparametric magnetic resonance imaging (mpMRI), present a clinical challenge due to their equivocal nature in predicting clinically significant prostate cancer (csPCa). Aim of the study is to improve risk stratification of patients with PI-RADS 3 lesions and candidates for prostate biopsy.

Methods: A cohort of 4841 consecutive patients who underwent MRI and subsequent MRI-targeted and systematic biopsies between January 2016 and April 2023 were retrospectively identified from independent prospectively maintained database. Only patients who have PI-RADS 3 lesions were included in the final analysis. A multivariable logistic regression analysis was performed to identify covariables associated with csPCa defined as International Society of Urological Pathology (ISUP) grade group ≥2. Performance of the model was evaluated using the area under the receiver operating characteristic curve (AUC), calibration, and net benefit. Significant predictors were then selected for further exploration using a Chi-squared Automatic Interaction Detection (CHAID) analysis.

Results: Overall, 790 patients had PI-RADS 3 lesions and 151 (19%) had csPCa. Significant associations were observed for age (OR: 1.1 [1.0-1.1]; p = 0.01) and PSA density (OR: 1643 [2717-41,997]; p < 0.01). The CHAID analysis identified PSAd as the sole significant factor influencing the decision tree. Cut-offs for PSAd were 0.13 ng/ml/cc (csPCa detection rate of 1% vs. 18%) for the two-nodes model and 0.09 ng/ml/cc and 0.16 ng/ml/cc for the three-nodes model (csPCa detection rate of 0.5% vs. 2% vs. 17%).

Conclusions: For individuals with PI-RADS 3 lesions on prostate mpMRI and a PSAd below 0.13, especially below 0.09, prostate biopsy can be omitted, in order to avoid unnecessary biopsy and overdiagnosis of non-csPCa.

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Conflict of interest statement

Competing interests: The authors declare no competing interests. Ethics approval and consent to participate: This research is in accordance with the Declaration of Helsinki and was conducted after IRB approval of our institution. A written informed consent was obtained from all subjects.

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