ArticleCancer medicine2023
Development and validation of a novel nomogram predicting clinically significant prostate cancer in biopsy-naive men based on multi-institutional analysis.
Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Development and validation of a clinical-radiomics model for prediction of prostate cancer: a multicenter study.World journal of urology · 2024Article
- Development and validation of a novel nomogram predicting clinically significant prostate cancer in biopsy-naive men based on multi-institutional analysis.Cancer medicine · 2023Article
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9 authors.
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Abstract
backgroundPrediction 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.
methodsIndependent 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.
resultsA 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
conclusionThis 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
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