| Objective:To explore the diagnostic efficacy of PI-RADS v2.1(prostate Imaging Report and Data System version2.1)score for PCa(prostate cancer)in patients with prostate volume >40ml.Materials and Methods:A retrospective study was conducted on patients who underwent prostate biopsy with PV>40ml from August 2019 to August 2022 at our center.After strict inclusion and exclusion criteria,a total of 86 patients were included.Using pathological results as the gold standard,patients were divided into a positive group of 38 and a negative group of 48.Age,Body mass index(BMI),prostate specific antigen(PSA),and Prostate specific antigen density were recorded in both groups density,PSAD,PI-RADS v2.1 scores and other clinical data.The measurement data were tested for normality first,and the measurement data conforming to the normal distribution were compared with the T-test of two independent samples.If the index does not conform to the normal distribution,the rank sum test of two independent samples is used.χ2test and Fisher’s exact probability method were used to compare the statistical data between groups.The selection of methods was determined by the data distribution,and P<0.05 was considered statistically significant.The independent prediction indicators of PCa were selected by multi-factor analysis.the Receiver Operating Characteristic curve(ROC)of each predictive index was plotted and the Area Under the ROC Curve(AUC)was calculated.To evaluate the diagnostic efficacy of each index in PCa with PV>40ml.Results:86 patients with PV>40ml were divided into a positive group of 38 and a negative group of 48 according to pathological findings.Age,BMI,PSA,PV,PSAD and PI-RADS v2.1 scores were compared between the two groups,and there were no statistical differences in age and PV between the two groups(all P >0.05),while there were statistical differences in BMI,PSA,PSAD and PI-RADS scores between the two groups(all P< 0.05).The scores of PSA,PSAD and PI-RADS were analyzed by binary univariate Logistic regression,and the independent predictor of PCa was PI-RADS v2.1 score(0R=4.059,95%CI: 2.035-8.095,P<0.05).PSA(0R=1.123,95%CI: 1.048-1.208,P<0.05);PSAD(0R=1.99,95%CI: 1.348-2.937,P<0.05).The AUC area under ROC curve was respectively PI-RADS v2.1 score(0.832),PSA(0.704),PSAD(0.728),and PI-RADS v2.1 score combined with PSAD(0.837).The analysis of diagnostic efficacy showed that the optimal cut-off value of PI-RADS score was PI-RADS score >3,and the Yoden index was 0.575,the sensitivity was0.658,and the specificity was 0.917.The optimal cut-off value of PSA index was17.85,and the Yoden index was 0.376,the sensitivity was 0.605 and the specificity was 0.771.The optimal truncation value of PSAD was 0.215,the Yoden index was0.378,the sensitivity was 0.711,and the specificity was 0.667.The optimal cut-off value of PI-RADS v2.1 score combined with PSAD diagnosis was 0.41,and the Yoden index was 0.596,the sensitivity was 0.763,and the specificity was 0.833.Conclusions:1.For patients with prostate volume >40ml,PI-RADS v2.1 scoring system is an independent predictor of PCa,and its predictive efficacy is stronger than that of PSA and PSAD.2.For patients with PV>40ml,the combined prediction system of PI-RADS v2.1 score and PSAD has better prediction effect than the single application of various indicators,and can effectively reduce unnecessary puncture. |
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