Research Article

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

Table 4

Multivariate logistic regression analyses of the base model and the improved model for predicting prostate cancer.

VariablesBase modelImproved model
OR (95% CI); OR (95% CI);

Age1.080 (1.010, 1.155); 0.0241.058 (0.978, 1.144); 0.159
Prostate volume0.979 (0.958, 1.001); 0.0630.984 (0.960, 1.009); 0.221
% fPSA0.001 (0.00001, 1.438): 0.0630.00001 (0, 0.277); 0.024
PCA31.008 (1.003, 1.012); 0.002
PGSR1.002 (1.000, 1.005); 0.036
MALAT-11.004 (1.001, 1.006); 0.003
PA (%)74.6%84.4%
Increment PA (%)9.8%
AUC (95% CI)0.733 (0.634, 0.831)0.857 (0.780, 0.933)
Increment AUC (95% CI)0.124

PCA3: prostate cancer antigen 3; PSGR: prostate-specific G protein coupled receptor; MALAT-1: metastasis-associated lung adenocarcinoma transcript 1; AUC: area under the curve; 95% CI: 95% confidential interval.