Integrating Prostate-Specific Antigen Density and Prostate Imaging Reporting and Data System Scores to Optimize Detection of Clinically Significant Prostate Cancer: A Multivariable Risk Model Approach.

BACKGROUND

Prebiopsy multiparametric MRI (mpMRI) reported using the Prostate Imaging Reporting and Data System (PI-RADS) improves prostate cancer triage, yet false-positive findings remain common and may drive unnecessary biopsy. Prostate-specific antigen density (PSAD) is an inexpensive laboratory-derived adjunct that may refine MRI-based risk stratification.

METHODS

We retrospectively screened 713 transrectal ultrasound (TRUS)-guided biopsy episodes from a single experienced urologist's practice at a tertiary referral hospital between October 2022 and August 2025 and included 375 men with prebiopsy mpMRI reported using PI-RADS version 2.1 and complete data for prespecified predictors. All patients underwent systematic 12-core TRUS-guided biopsy. Clinically significant prostate cancer (csPCa) was defined as International Society of Urological Pathology (ISUP) grade group ≥ 2. We developed logistic regression models combining PSAD and PI-RADS (parsimonious model) and adding age and digital rectal examination (DRE) (full model). Discrimination (AUC), calibration, and clinical utility (decision curve analysis) were assessed, and the incremental value of PSAD beyond PI-RADS for csPCa was quantified using IDI and continuous NRI.

RESULTS

csPCa was present in 93/375 (24.8%) and any prostate cancer in 144/375 (38.4%). For csPCa prediction, AUC was 0.746 for PI-RADS and 0.760 for PSAD; the combined PSAD+PI-RADS model achieved AUC 0.798 and the full model AUC 0.794. Adding PSAD to PI-RADS improved IDI (0.0528; p < 0.001) and total continuous NRI (0.3926; p < 0.001), driven mainly by improved down-classification of non-csPCa cases.

CONCLUSIONS

Integrating PSAD with PI-RADS improved csPCa risk stratification compared with PI-RADS alone, with predominant benefit as a biopsy-sparing, rule-out adjunct. External validation is required for clinical implementation.