ArticleWorld journal of surgical oncology2023
Developing a predictive model for clinically significant prostate cancer by combining age, PSA density, and mpMRI.
Article in World journal of surgical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Risk calculators for the detection of prostate cancer: a systematic review.Prostate cancer and prostatic diseases · 2024Pooled it
- Evaluation of MRI-based risk models versus PI-RADS version 2.1 and arterial spin labeling perfusion imaging strategy for clinically significant prostate cancer.Quantitative imaging in medicine and surgery · 2026Article
- PI-RADS v2.1 for prostate MRI: current applications, ongoing debates, and synergies with advanced technologies-a narrative review.Translational andrology and urology · 2026Review
- Urinary Epithelial Cell Adhesion Molecule (EpCAM) as a Noninvasive Biomarker for Detecting Clinically Significant Prostate Cancer in Men With Equivocal PSA Levels.BioMed research international · 2026Article
- PI-RADSv2.1 combined with PSA density for optimizing prostate biopsy decisions: a retrospective analysis.Frontiers in oncology · 2025Article
- Challenges in magnetic resonance imaging-based detection of clinically significant prostate cancer in young patients: two alternative approaches.Quantitative imaging in medicine and surgery · 2024Article
- Prior Negative Biopsy, PSA Density, and Anatomic Location Impact Cancer Detection Rate of MRI-Targeted PI-RADS Index Lesions.Current oncology (Toronto, Ont.) · 2024Article
- Long-term follow-up results of multiparametric prostate MRI and the prognostic value of PI-RADS: a single-center retrospective cohort studyDiagnostic and interventional radiology (Ankara, Turkey) · 2024Article
- Development and validation of a nomogram prediction model for clinically significant prostate cancer combined with PI-RADS V2.1, MRI quantitative parameters and clinical indicators: a two-center study.Frontiers in oncology · 2024Article
- Reliability of Systematic and Targeted Biopsies versus Prostatectomy.Bioengineering (Basel, Switzerland) · 2023Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe study aimed to construct a predictive model for clinically significant prostate cancer (csPCa) and investigate its clinical efficacy to reduce unnecessary prostate biopsies.
methodsA total of 847 patients from institute 1 were included in cohort 1 for model development. Cohort 2 included a total of 208 patients from institute 2 for external validation of the model. The data obtained were used for retrospective analysis. The results of magnetic resonance imaging were obtained using Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1). Univariate and multivariate analyses were performed to determine significant predictors of csPCa. The diagnostic performances were compared using the receiver operating characteristic (ROC) curve and decision curve analyses.
resultsAge, prostate-specific antigen density (PSAD), and PI-RADS v2.1 scores were used as predictors of the model. In the development cohort, the areas under the ROC curve (AUC) for csPCa about age, PSAD, PI-RADS v2.1 scores, and the model were 0.675, 0.823, 0.875, and 0.938, respectively. In the external validation cohort, the AUC values predicted by the four were 0.619, 0.811, 0.863, and 0.914, respectively. Decision curve analysis revealed that the clear net benefit of the model was higher than PI-RADS v2.1 scores and PSAD. The model significantly reduced unnecessary prostate biopsies within the risk threshold of > 10%.
conclusionsIn both internal and external validation, the model constructed by combining age, PSAD, and PI-RADS v2.1 scores exhibited excellent clinical efficacy and can be utilized to reduce unnecessary prostate biopsies.
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