Developing A Nomogram To Predict The Risk Of Clinically Significant Prostate Cancer In Men With PSA<10 Ng/ml At First Biopsy

Objective:To develop a nomogram to predict the risk of clinically significant prostate cancer(csPCa)in men with PSA<10 ng/ml at first biopsy.To determine whether this novel nomogram combined PIRADS v2 and neutrophil-to-lymphocyte ratio(NLR)improves the detection of csPCa.Methods:Univariable and multivariable binary logistic regression analysis were used to screen for independent risk factors of csPCa.The multivariable model based on the risk factors was to build the nomogram predicting csPCa and assessed by receiver operator characteristic(ROC)curve analysis,calibration plot and decision curve analysis(DCA).Results:This retrospective study included 335 men with PSA<10 ng/ml who underwent initial biopsy.A total of 78(23.3%)men had csPCa.The nomogram was built based on the multivariable model including age,DRE,%fPSA,PIRADS v2 and NLR.It had high AUC of 0.876 and was well calibrated in internal validation.DCA also demonstrated that it would improve the prediction of csPCa.Conclusion:PIRADS v2 and NLR improve the detection of csPCa in men with PSA<10 ng/ml at first biopsy.Due to lack of external validation,relatively small cohort and homogenous population,the study has several limitations.Despite of this,the nomogram based on our study is a promising tool for patients to understand their risk of csPCa and for urologists to make clinical decision.