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

  • 期刊论文

  • 发表日期：

    2024年7月24日

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  • Georges Mjaess,
  • Laura Haddad,
  • Teddy Jabbour,
  • Arthur Baudewyns,
  • Henri-Alexandre Bourgeno,
  • Yolène Lefebvre,
  • Mariaconsiglia Ferriero,
  • Giuseppe Simone,
  • Alexandre Fourcade,
  • Georges Fournier,
  • Marco Oderda,
  • Paolo Gontero,
  • Adrian Bernal-Gomez,
  • Alessandro Mastrorosa,
  • Jean-Baptiste Roche,
  • Rawad Abou Zahr,
  • Guillaume Ploussard,
  • Gaelle Fiard,
  • Adam Halinski,
  • Katerina Rysankova,
  • Charles Dariane,
  • Gina Delavar,
  • Julien Anract,
  • Nicolas Barry Delongchamps,
  • Alexandre Patrick Bui,
  • Fayek Taha,
  • Olivier Windisch,
  • Daniel Benamran,
  • Gregoire Assenmacher,
  • Jan Benijts,
  • Karsten Guenzel,
  • Thierry Roumeguère,
  • Alexandre Peltier,
  • Romain Diamand

摘要

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.