Analysis of influential factors for prostate biopsy and establishment of logistic regression model for 
prostate cancer

Objective: To establish logistic regression model for prostate cancer and provide basis for prostate biopsy.


Methods: A total of 117 cases of prostate biopsy were retrospectively analyzed in chronological sequence. All cases were assigned into a model group (n=78) and a validation group (n=39). Logistic regression model was established and its value was estimated by receiver operating characteristic (ROC) curve. 


Results: Digital rectal examination(DRE), transrectal ultrasound(TRUS), MRI, prostate-specific antigen density (PSAD), and free PSA/total PSA (fPSA/tPSA) were the influential factors for prostate biopsy (P<0.01). The established logistic regression model for prostate cancer by regression coefficient was: logit P=-2.362+2.561×DRE+1.747×TRUS+2.901×MRI+1.126×PSAD-
2.569×fPSA/tPSA and area under curve was 0.907. When the cutoff aimed at 0.12, the sensitivity and specificity were 81.80% and 89.30%, respectively.


Conclusions: Logistic regression model for prostate cancer can provide sufficient basis for prostate biopsy. Prostate biopsy should be performed when P value is more than 0.12.