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Fig. 1 | BMC Urology

Fig. 1

From: Elucidating the need for prostate cancer risk calculators in conjunction with mpMRI in initial risk assessment before prostate biopsy at a tertiary prostate cancer center

Fig. 1

ROC curves for PCa and csPCa detection by multivariate risk models and mpMRI. ROC curve analysis of PI-RADS score, ERSPC-RC3, MRI-ERSPC-RC3, Radtke-RC and MSP-RC before initial prostate biopsy comparing healthy patients and men with proven PCa (A) and proven csPCa (B) is illustrated. In detail, ERSPC-RC3 (PCa: AUC 0.68, 95%CI 0.63–0.72, sensitivity 70%, specificity 61%; csPCa: AUC 0.76, 95%CI 0.72–0.80, sensitivity 65%, specificity 74%; MRI-ERSPC-RC3 (PCa: AUC 0.80, 95%CI 0.76–0.84, sensitivity 73%, specificity 73%; csPCa: AUC 0.84, 95%CI 0.81–0.87, sensitivity 80%, specificity 74%); MSP-RC (PCa: AUC 0.82, 95%CI 0.78–0.86, sensitivity 75%, specificity 78%; csPCa: AUC 0.82, 95%CI 0.79–0.86, sensitivity 78%, specificity 74%); Radtke-RC (PCa: AUC 0.82, 95%CI 0.78–0.86, sensitivity 75%, specificity 76%; csPCa: AUC 0.84, 95%CI 0.81–0.87, sensitivity 85%, specificity 65%); PI-RADS (PCa: AUC of 0.81,95%CI 0.77–0.84, sensitivity 82%, specificity 70%; csPCa: AUC 0.82, 95%CI 0.79–0.86, sensitivity 87%, specificity 68%)

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BMC Urology

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