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.
| Variables | OR (95% CI); | AUC (95% CI) |
| Age | 1.089 (1.0227, 1.160); 0.004 | 0.668 (0.577, 0.750) | PSA | 0.945 (0.747, 1.197); 0.640 | 0.525 (0.408, 0.642) | Prostate volume | 0.975 (0.954, 0.996); 0.020 | 0.657 (0.566, 0.741) | % fPSA | 0.0003 (0, 0.241); 0.018 | 0.617 (0.524, 0.703) | DRE | 1.725 (0.717, 4.152); 0.224 | 0.554 (0.437, 0.672) | PCA3 | 1.006 (1.002, 1.010); 0.001 | 0.734 (0.641, 0.828) | PGSR | 1.002 (1.000, 1.004); 0.026 | 0.666 (0.575, 0.749) | PSMA | 0.999 (0.995, 1.003); 0.621 | 0.516 (0.398, 0.634) | MALAT-1 | 1.003 (1.001, 1.005); 0.002 | 0.727 (0.625, 0.829) |
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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.
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