Diagnostic Value Of PI-RADS V2.1 And Prostate Health Index In PSA Gray Area Prostate Cancer

Objective To evaluate the diagnostic value of multiparameter magnetic resonance(mpMRI)prostate imaging reporting and data system(PI-RADS)v2.1 and prostate health index(PHI)for clinically significant prostate cancer(CSPCa)at serum prostate specific antigen(PSA)grey area(4-10ng/mL).To analyze the diagnostic value of free prostate specific antigen ratio(%fPSA),PHI,PSA density(PSAD)and PI-RADS score for CSPCa in the PSA grey area.PI-RADS score and PHI was used to establish a predictive model for CSPCa to reduce unnecessary biopsy.Methods A total of 142 patients who underwent prostate biopsy at Qilu Hospital of Shandong University from August 2019 to October 2021 were consecutively enrolled in the study.Clinical data were collected and all patients were divided into positive group and negative group according to pathological reports and mpMRI.SPSS 25.0 and MedCalc statistical software were used for statistical analysis.Pearson Chi-square test was used to evaluate the differences between categorical variables.Student’s T test and Mann-Whitney U test were used to compare the normal and non-normal continuous variables,respectively.Binary logistic regression was used to analyze the predictive the diagnostic value of each variable for CSPCa.PHI and PI-RADS scores were added into binary logistic regression to establish a prediction model Logit(P)for CSPCa.The receiver operating characteristic curves of each variable and the prediction model Logit(P)were drawn.Delong test was used to analyze the statistical difference between Logit(P)and the area under the curve(AUC)of each variable.The optimal truncation value was determined on Youden index of each variable.Then the sensitivity,specificity,positive predictive value(PPV)and negative predictive value(NPV)of each variable in the diagnosis of CSPCa were calculated.McNemar test was used to compare the differences in the diagnostic tests of each variable.Results 142 patients were eventually enrolled,including 41 patients with CSPCa in the positive group,9 patients with clinically insignificant prostate cancer(CISPCa)and 92 patients with benign prostatic hyperplasia in the negative group.There were no significant differences in PSA level,age,body mass index,smoking history and drinking history between two groups(p>0.05).There was no significant difference in PSAD between positive group and negative group(p=0.071).PI-RADS score,PHI and%fPSA had significant predictive ability for CSPCa(p<0.05).The area under curve(AUC)of PHI and PI-RADS scores was higher than%fPSA.A predictive model of PHI combined with PI-RADS score was established by binary logistic regression analysis:Logit(P)=1.12×PI-RADS score+0.05×PHI-6.29.The AUC of Logit(P)was significantly higher than that of%fPSA,PHI and PI-RADS scores,and the differences were statistically significant(p<0.05).Diagnostic tests showed that Logit(P)had a higher sensitivity(78.05%)than PI-RADS score and PHI,and a higher specificity(81.19%)than PHI.The PPV and NPV of Logit(P)were 62、75%and 96.70%,respectively.Conclusion In PSA 4-10ng/mL patients,mpMRI PI-RADS score had high specificity and PPV in CSPCa screening,but its sensitivity was relatively low.PHI was more sensitive to CSPCa than%fPSA and PI-RADS scores.Logit(P),a model to predict CSPCa established by PI-RADS score combined with PHI,has high PPV and sensitivity,reduces the rate of missed diagnosis and unnecessary prostate biopsy,and can be used to guide prostate cancer screening.