Abstract
BACKGROUND: Prediction of clinically significant prostate cancer (csPCa) is essential to select biopsy-naive patients for prostate biopsy. This study was to develop and validate a nomogram based on clinicodemographic parameters and exclude csPCa using prostate-specific antigen density (PSAD) stratification. METHODS: Independent predictors were determined via univariate and multivariate logistic analysis and adopted for developing a predictive nomogram, which was assessed in terms of discrimination, calibration, and net benefit. Different PSAD thresholds were used for deciding immediate biopsies in patients with Prostate Imaging-Reporting and Data System (PI-RADS) 3 lesions. RESULTS: A total of 932 consecutive patients who underwent ultrasound-guided transperineal cognitive biopsy were enrolled in our study. In the development cohort, age (odds ratio [OR], 1.075; 95% confidence interval [CI], 1.036-1.114), PSAD (OR, 6.003; 95% CI, 2.826-12.751), and PI-RADS (OR, 3.419; 95% CI, 2.453-4.766) were significant predictors for csPCa. On internal and external validation, this nomogram showed high areas under the curve of 0.943, 0.922, and 0.897, and low Brier scores of 0.092, 0.102, and 0.133 and insignificant unreliability tests of 0.713, 0.490, and 0.859, respectively. Decision curve analysis revealed this model could markedly improve clinical net benefit. The probability of excluding csPCa was 98.51% in patients with PI-RADS 3 lesions and PSAD <0.2 ng/ml(2) . CONCLUSION: This novel nomogram including age, PSAD, and PI-RADS could be applied to accurately predict csPCa, and 44.08% of patients with equivocal imaging findings plus PSAD <0.2 ng/ml(2) could safely forgo biopsy.