Research Article

Urinary Biomarker Panel to Improve Accuracy in Predicting Prostate Biopsy Result in Chinese Men with PSA 4–10 ng/mL

Table 2

Univariate logistic regression analyses of predictors for predicting prostate cancer.

VariablesOR (95% CI); AUC (95% CI)

Age1.089 (1.0227, 1.160); 0.0040.668 (0.577, 0.750)
PSA0.945 (0.747, 1.197); 0.6400.525 (0.408, 0.642)
Prostate volume0.975 (0.954, 0.996); 0.0200.657 (0.566, 0.741)
% fPSA0.0003 (0, 0.241); 0.0180.617 (0.524, 0.703)
DRE1.725 (0.717, 4.152); 0.2240.554 (0.437, 0.672)
PCA31.006 (1.002, 1.010); 0.0010.734 (0.641, 0.828)
PGSR1.002 (1.000, 1.004); 0.0260.666 (0.575, 0.749)
PSMA0.999 (0.995, 1.003); 0.6210.516 (0.398, 0.634)
MALAT-11.003 (1.001, 1.005); 0.0020.727 (0.625, 0.829)

PSA: prostate-specific antigen; % fPSA: percent free PSA; DRE: positive digital rectal examination results; PCA3: prostate cancer antigen 3; PSGR: prostate-specific G protein coupled receptor; PSMA: prostate-specific membrane antigen; MALAT-1: metastasis-associated lung adenocarcinoma transcript 1.