Optimizing Biopsy Decisions in PI-RADS 3-4 Lesions: Integrating PSA-derived Biomarkers to Reduce Unnecessary...

Prostate cancer is a common malignancy among men. However, identifying clinically significant prostate cancer (csPCa) remains challenging, particularly in the Prostate Imaging Reporting and Data System (PI-RADS) 3-4 lesions. This study evaluated whether combining prostate-specific antigen (PSA)-derived biomarkers and clinical parameters with multiparametric magnetic resonance imaging (mpMRI) improves risk stratification and reduces unnecessary biopsies.

Comprehensive clinical data of 165 patients who underwent mpMRI and MRI-ultrasound fusion-guided prostate biopsy between 2021 and 2024 was retrospectively analyzed. Patients were stratified by PI-RADS scores into two groups: 3-4 and 5. csPCa was defined as International Society of Urological Pathology grade group 2 or higher. Logistic regression models were used to identify predictors of csPCa. The diagnostic utility of PI-RADS scores alone and in combination with PSA density and PSA velocity was evaluated through receiver operating characteristic curves and decision curve analysis (DCA).

csPCa was detected in 30.8% of PI-RADS 3-4 lesions. PSA density was identified as an independent predictor [odds ratio (OR)=2.301, p=0.034]. In the PI-RADS 3-4 subgroup, the combination of PSA density and PSA velocity achieved an area under the curve of 0.673. DCA showed that the combined model provided the highest net benefit within the 18%-50% threshold range, reducing unnecessary biopsies by 68.0% while missing 33.3% of csPCa cases.

Integrating PSA density and PSA velocity improves diagnostic performance in PI-RADS 3-4 lesions. This approach may assist in clinical decision-making by reducing over-biopsy while maintaining acceptable sensitivity for detecting csPCa.