Analysis Of Predictive Factors Of Positive Prostate Biopsy In Gray Area Of PSA And Preliminary Construction Of Predictive Model

Objective: To study the independent predictive factors of the positive results of transperineal prostate biopsy in PSA gray area patients,and build a predictive model of PSA gray area prostate cancer(nomogram).To assess the risk of prostate cancer for patients with PSA gray area,and to help decide whether further prostate puncture is necessary.Methods: The clinical data of PSA gray area patients who underwent transperineal prostate biopsy in the urology department of our hospital from December 2020 to December 2022 were collected.According to the puncture pathology,they were divided into group A(PCa group)and group B(non PCa group).Shapiro Wilk Test was used to determine whether the measurement data belonged to normal distribution;The data conforming to the normal distribution are represented by mean ± standard deviation,and compared by independent sample t-test;Continuous variables of non normal distribution are expressed in the form of median and interquartile interval,and compared with Mann Whitney U test;For discontinuous variables,expressed by rate(%),chi square test is used;Single factor and multi factor logistic regression analysis were used to screen independent predictive factors and establish a prediction model(nomograph)based on independent predictive factors.The performance of the model was evaluated by ROC curve,calibration curve and Hosmer Leisshow test.The decision curve analysis(DCA)and clinical impact curve were used to evaluate the net benefits of the model under different threshold probabilities.SPSS 26.0 and R software were used to analyze data and draw graphs.P < 0.05 was considered as statistically significant difference.Results: 1.A total of 191 patients were included in the statistical analysis,including 53 patients in the PCa group(27.75%)and 138 patients in the non PCa group(72.25%).Univariate and multivariate logistic regression analysis showed that age and PI-RADS score were independent risk factors for prostate cancer,and prostate volume(PV)was a protective factor for prostate cancer(PV is negatively correlated with the risk of PCa).The area under the ROC curve(AUC)of age,PI-RADS score and PV were 0.651,0.795 and 0.696 respectively.2.According to the screened independent predictors,a prediction model of prostate cancer in the gray area of PSA was constructed.The area under the ROC curve(AUC)of this model was 0.856,and the 95% CI was 0.789-0.923),which was higher than the AUC of a single independent predictor.The prediction model was tested,and the calibration curve showed good consistency.The model fitting index,the Hosmer Lemesow test(H-L test),showed that: X-squared=0.37485,df=1,P>0.05,there was no statistical difference,It is suggested that there is no significant difference between the predicted results and the actual results.According to the analysis of decision curve,the model is beneficial and feasible in clinical practice.The clinical impact curve(CIC)shows that when the risk probability threshold is 40%,the loss benefit ratio is 2:3.When the risk probability threshold is greater than 40%,the maximum net income can be obtained.Conclusion: 1.Age,prostate volume(PV)and PI-RADS score are independent risk factors of prostate cancer in PSA gray area,which have certain significance in predicting prostate cancer.2.This study provides a good nomograph,which can predict the probability of prostate cancer in patients with PSA gray area before operation,help us clinicians and patients to jointly choose whether to conduct prostate puncture biopsy,and provide a simple and non-invasive method for male prostate cancer screening.