title: The impact of biomarkers in multivariate algorithms for bladder cancer diagnosis in patients with hematuria.
abstract: BACKGROUND
  We appraised 23 biomarkers previously associated with urothelial cancer in a case-control study. Our aim was to determine whether single biomarkers and/or multivariate algorithms significantly improved on the predictive power of an algorithm based on demographics for prediction of urothelial cancer in patients presenting with hematuria.
  
  
  METHODS
  Twenty-two biomarkers in urine and carcinoembryonic antigen (CEA) in serum were evaluated using enzyme-linked immunosorbent assays (ELISAs) and biochip array technology in 2 patient cohorts: 80 patients with urothelial cancer, and 77 controls with confounding pathologies. We used Forward Wald binary logistic regression analyses to create algorithms based on demographic variables designated prior predicted probability (PPP) and multivariate algorithms, which included PPP as a single variable. Areas under the curve (AUC) were determined after receiver-operator characteristic (ROC) analysis for single biomarkers and algorithms.
  
  
  RESULTS
  After univariate analysis, 9 biomarkers were differentially expressed (t test; P < .05). CEA AUC 0.74; bladder tumor antigen (BTA) AUC 0.74; and nuclear matrix protein (NMP22) 0.79. PPP included age and smoking years; AUC 0.76. An algorithm including PPP, NMP22, and epidermal growth factor (EGF) significantly improved AUC to 0.90 when compared with PPP. The algorithm including PPP, BTA, CEA, and thrombomodulin (TM) increased AUC to 0.86. Sensitivities = 91%, 91%; and specificities = 80%, 71%, respectively, for the algorithms.
  
  
  CONCLUSIONS
  Addition of biomarkers representing diverse carcinogenic pathways can significantly impact on the ROC statistic based on demographics. Benign prostate hyperplasia was a significant confounding pathology and identification of nonmuscle invasive urothelial cancer remains a challenge.
authors.affiliation: Centre for Cancer Research & Cell Biology, Queens University Belfast, Belfast, Ireland.
authors.forename: Funso
authors.initials: F
authors.lastname: Abogunrin
authors.forename: Hugh F
authors.initials: HF
authors.lastname: O'Kane
authors.forename: Mark W
authors.initials: MW
authors.lastname: Ruddock
authors.forename: Michael
authors.initials: M
authors.lastname: Stevenson
authors.forename: Cherith N
authors.initials: CN
authors.lastname: Reid
authors.forename: Joe M
authors.initials: JM
authors.lastname: O'Sullivan
authors.forename: Neil H
authors.initials: NH
authors.lastname: Anderson
authors.forename: Declan
authors.initials: D
authors.lastname: O'Rourke
authors.forename: Brian
authors.initials: B
authors.lastname: Duggan
authors.forename: John V
authors.initials: JV
authors.lastname: Lamont
authors.forename: Ruth E
authors.initials: RE
authors.lastname: Boyd
authors.forename: Peter
authors.initials: P
authors.lastname: Hamilton
authors.forename: Thiagarajan
authors.initials: T
authors.lastname: Nambirajan
authors.forename: Kate E
authors.initials: KE
authors.lastname: Williamson
mesh_terms: D000368:Aged; D000465:Algorithms; D014408:Biomarkers, Tumor / Q000652:urine*; D002272:Carcinoembryonic Antigen / Q000097:blood*; D016022:Case-Control Studies; D005260:Female; D006417:Hematuria / Q000175:diagnosis*; D006801:Humans; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011336:Probability; D011446:Prospective Studies; D012372:ROC Curve; D001749:Urinary Bladder Neoplasms / Q000175:diagnosis*
chemical_list: D014408:Biomarkers, Tumor; D002272:Carcinoembryonic Antigen