Accurate urinary assays for bladder cancer (BCa) detection would benefit both 
patients and healthcare systems. Through genomic and proteomic profiling of 
urine components, we have previously identified a panel of biomarkers that can 
outperform current urine-based biomarkers for the non-invasive detection of BCa. 
Herein, we report the diagnostic utility of various multivariate combinations of 
these biomarkers. We performed a case-controlled validation study in which 
voided urines from 127 patients (64 tumor bearing subjects) were analyzed. The 
urinary concentrations of 14 biomarkers (IL-8, MMP-9, MMP-10, SDC1, CCL18, 
PAI-1, CD44, VEGF, ANG, CA9, A1AT, OPN, PTX3, and APOE) were assessed by 
enzyme-linked immunosorbent assay (ELISA). Diagnostic performance of each 
biomarker and multivariate models were compared using receiver operating 
characteristic curves and the chi-square test. An 8-biomarker model achieved the 
most accurate BCa diagnosis (sensitivity 92%, specificity 97%), but a 
combination of 3 of the 8 biomarkers (IL-8, VEGF, and APOE) was also highly 
accurate (sensitivity 90%, specificity 97%). For comparison, the commercial 
BTA-Trak ELISA test achieved a sensitivity of 79% and a specificity of 83%, and 
voided urine cytology detected only 33% of BCa cases in the same cohort. These 
data show that a multivariate urine-based assay can markedly improve the 
accuracy of non-invasive BCa detection. Further validation studies are under way 
to investigate the clinical utility of this panel of biomarkers for BCa 
diagnosis and disease monitoring.