Cancer · 2022 · 42 citations · 20 references
MedicineRadiologyUrologyDiagnostic ImagingDiagnostic RadiologyGenitourinary RadiologyProstate BiopsyProstate CancerProstate ImagingProstate PathologyProstate-specific Antigen TestingUrologic Cancer DiagnosisClinical Utility AnalysisClinical Utility AssessmentClinically Significant Prostate Cancer DetectionLogistic RegressionMagnetic Resonance Imaging - Targeted BiopsyProstate Cancer PrognosisProstate Cancer Risk StratificationProstate-specific Antigen Density
BACKGROUND: Most Prostate Imaging-Reporting and Data System (PI-RADS) 3 lesions do not contain clinically significant prostate cancer (CSPCa; grade group ≥2). This study was aimed at identifying clinical and magnetic resonance imaging (MRI)-derived risk fac- tors that predict CSPCa in men with PI-RADS 3 lesions. METHODS: This study analyzed the detection of CSPCa in men who underwent MRI-targeted biopsy for PI-RADS 3 lesions. Multivariable logistic regression models with goodness-of-fit testing were used to identify variables associated with CSPCa. Receiver operating curves and decision curve analyses were used to estimate the clinical utility of a predictive model. RESULTS: Of the 1784 men reviewed, 1537 were included in the training cohort, and 247 were included in the validation cohort. The 309 men with CSPCa (17.3%) were older, had a higher prostate-specific antigen (PSA) density, and had a greater likelihood of an anteriorly located lesion than men without CSPCa (p < .01). Multivariable analysis revealed that PSA density (odds ratio [OR], 1.36; 95% confidence interval [CI], 1.05-1.85; p < .01), age (OR, 1.05; 95% CI, 1.02-1.07; p < .01), and a biopsy-naive status (OR, 1.83; 95% CI, 1.38-2.44) were independently associated with CSPCa. A prior negative biopsy was negatively associated (OR, 0.35; 95% CI, 0.24-0.50; p < .01). The application of the model to the validation cohort resulted in an area under the curve of 0.78. A predicted risk threshold of 12% could have prevented 25% of biopsies while detecting almost 95% of CSPCas with a sensitivity of 94% and a specificity of 34%. CONCLUSIONS: For PI-RADS 3 lesions, an elevated PSA density, older age, and a biopsy-naive status were associated with CSPCa, whereas a prior negative biopsy was negatively associated. A predictive model could prevent PI-RADS 3 biopsies while missing few CSPCas. LAY SUMMARY: Among men with an equivocal lesion (Prostate Imaging-Reporting and Data System 3) on multiparametric magnetic resonance imaging (mpMRI), those who are older, those who have a higher prostate-specific antigen density, and those who have never had a biopsy before are at higher risk for having clinically significant prostate cancer (CSPCa) on subsequent biopsy. However, men with at least one negative biopsy have a lower risk of CSPCa. A new predictive model can greatly reduce the need to biopsy equivocal lesions noted on mpMRI while missing only a few cases of CSPCa.
20
pROC: an open-source package for R and S+ to analyze and compare ROC curves
Xavier Robin, Natacha Turck, Alexandre Hainard et al. · BMC Bioinformatics · 2011 · 14K citations · Full text
MRI-Targeted or Standard Biopsy for Prostate-Cancer Diagnosis
Veeru Kasivisvanathan, Antti Rannikko, Marcelo Borghi et al. · New England Journal of Medicine · 2018 · 3K citations · Full text
PI-RADS Prostate Imaging – Reporting and Data System: 2015, Version 2
Jeffrey C. Weinreb, Jelle O. Barentsz, Peter L. Choyke et al. · European Urology · 2015 · 2.9K citations
Barış Türkbey, Haresh Mani, Vijay Shah et al. · The Journal of Urology · 2011 · 499 citations · Full text