We then constructed a receiver operating characteristic curve (ROC) based on a random forest algorithm and calculated the area under it (i.e., the AUC), where the results showed SERPINA3, LRG1, and SCGB3A1 added classified value (added AUC; 0.09, 0.02, 0.04, respectively) in addition to age, prostate size, BMI, and PSA, suggesting the clinical value by incorporating EV biomarkers in prostate cancer diagnosis (Figure 5d). This evidence concerns the gene SERPINA3 and prostate cancer.