Keywords: Prostate, Prostate, Clinically Significant Prostate cancer,PSA density,PSA gray zone,PI-RADS v2.1
Motivation: It is crucial to improve the accuracy of detection of clinically significant prostate cancer (csPCa) within the PSA gray zone.
Goal(s): To combine PI-RADS v2.1 with prostate-specific antigen density(PSAD) derivatives to improve the predictive value of csPCa in the PSA gray zone.
Approach: Based on a dual-center study, logistic regression was used to analyze the predictive value of the multi-parameter combination on csPCa in the training group, the receiver operating characteristic curve(ROC) curves were used to evaluate the diagnostic performance, and conducting external validation.
Results: The area under curve (AUC) of combining of PI-RADS v2.1 and PSAD was the highest for predicting csPCa.
Impact: The dual-center study demonstrates combining of PI-RADS v2.1 and PSAD improved the predictive performance of csPCa in the PSA gray zone, and grouping PSAD with PI-RADS risk stratification can have more direct clinical applications.
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