Integrated Assessment of Percentage α2,3-Linked Sialylated Prostate-specific Antigen and the Prostate Health Index with Magnetic Resonance Imaging for Detection of Clinically Significant Prostate Cancer.

Background and objective: The diagnostic roles of serum percentage α2,3-linked sialylated prostate-specific antigen (S2,3PSA%) and the Prostate Health Index (PHI) in predicting clinically significant prostate cancer (csPC) remain unclear in the context of magnetic resonance imaging (MRI)-guided biopsy. Our aim was to evaluate the associations of S2,3PSA% and PHI with csPC and to develop an internally validated nomogram that integrates these biomarkers with prostate MRI. Methods: This retrospective single-center study included 248 consecutive men who underwent both S2,3PSA% and PHI testing, followed by MRI-ultrasound fusion targeted biopsy between October 2018 and July 2025. We used multivariable logistic regression models to identify predictors of csPC (Gleason ≥7). Internal validation was conducted with 1000 bootstrap resamples to estimate optimism and calculate the optimism-corrected area under the receiver operating characteristic curve (AUC), calibration slope, and Brier score. Decision curve analysis (DCA) was used to assess the clinical net benefit of the nomogram. Key findings and limitations: Among 248 patients, csPC was detected in 111 (45%). Age, S2,3PSA%, and Prostate Imaging-Reporting and Data System (PI-RADS) score were independent predictors of csPC. The nomogram achieved an apparent AUC of 0.857. Internal bootstrap validation yielded an optimism-corrected AUC of 0.783, calibration slope of 0.911, and Brier score of 0.139, which confirm good model discrimination and calibration. DCA demonstrated a clear net benefit for the nomogram across clinically relevant threshold probabilities. The single-center design and lack of external validation limit the generalizability of our results. Conclusions and clinical implications: Integration of S2,3PSA%, PHI, and PI-RADS scores provides incremental diagnostic utility for csPC detection. Internally validated models suggested better discrimination on integration of these biomarkers with MRI. However, these findings are exploratory and require external validation. Patient summary: We found that combining blood biomarkers called S2,3PSA% and the Prostate Health Index with MRI (magnetic resonance imaging) scan findings improved prediction of whether a patient has prostate cancer. Larger studies are needed to confirm our results.