Diagnostic Prediction Model And Follow-up Mechanism Of PSA “grey Area” Prostate Cancer In Han Chinese Men In Southern China

Objective To establish a new PSA "gray area" prostate cancer early prediction model for the Han Chinese men in southern China,combined with the commonly used detection indexes in clinical work,and apply it to the clinic to establish a prostate cancer puncture follow-up mechanism.Methods The first stage: retrospective study of the clinical data of patients with PSA values in the gray area and hospitalized perineal prostate biopsy from January 2008 to January 2018,a total of 502 cases.The age,total PSA,free PSA(f PSA),free PSA to total PSA ratio(f/t PSA),red blood cell distribution width(RDW),prostate volume(PV),prostate specific antigen density(PSAD),(f /t PSA)/PSAD,transrectal prostate ultrasound(TRUS),prostate magnetic resonance and enhancement(MRI),transrectal organ contrast echocardiography.According to the biopsy pathological results of the patients,the factors were analyzed by univariate analysis,and the logistic regression analysis was used for multi-factor analysis and screening of potential predictors.The PSA “gray area” prostate cancer diagnosis model was established.Through the receiver operating characteristic(ROC)curve,the diagnostic efficiency of the established predictive model was evaluated,and the risk value was determined based on the specificity and sensitivity,and the patients were divided into high risk group and low risk group.The second stage: using the newly established predictive model,a risk assessment of 151 patients with PSA “grey area” in our hospital from February 2018 to December 2018,and a prostate biopsy for patients in the high-risk group,for low risk The patient informed that there was a temporary close follow-up.Improve the predictive model and establish a prostate cancer puncture follow-up mechanism.Results Combining the two-stage data,the prediction model we obtained is:(?)It includes age,PSA,prostate volume,transrectal prostate ultrasound,prostate magnetic resonance and enhancement,transrectal prostate ultrasound,etc.,and the area under the new predictive model receiver operating characteristic(ROC)curve is 0.820.Compared with the traditional PSA and PSAD curves,the area is significantly increased(P<0.001),and the diagnostic efficiency is higher.Conclusions We established an early prediction model for PSA “gray area” prostate cancer for Han Chinese men in southern China.The diagnostic efficacy is higher than the traditional PSA predictive index,and it can predict the prostate cancer risk value of PSA “grey area” patients in clinical work.At the same time,establishing a prostate cancer puncture follow-up mechanism can reduce unnecessary needle biopsy and improve the detection rate of prostate cancer without delaying the diagnosis and treatment of patients.