title: Immunocytology is a strong predictor of bladder cancer presence in patients with painless hematuria: a multicentre study.
abstract: BACKGROUND
  Although the performance of immunocytology has been established in the surveillance of patients with urothelial carcinoma of the bladder (UCB), its value in the initial detection of UCB in patients with painless hematuria remains unclear.
  
  
  OBJECTIVE
  To determine whether immunocytology improves our ability to predict the likelihood of UCB in patients with painless hematuria. Further, to test the clinical benefit of immunocytology in this setting using decision curve analysis.
  
  
  METHODS
  The subjects were 1182 consecutive patients without a history of UCB presenting with painless hematuria and were enrolled at three centres.
  
  
  METHODS
  All patients underwent upper-tract imaging, cystourethroscopy, voided urine cytology, and immunocytology analysis. Bladder tumors were biopsied and histologically confirmed as UCB.
  
  
  METHODS
  Multivariable regression models were developed. Area under the curve was measured and compared using the DeLong test. A nomogram was constructed from the full multivariable model. Decision curve analysis was performed to evaluate the clinical benefit associated with use of the multivariable models including immunocytology.
  
  
  CONCLUSIONS
  Immunocytology had the largest contribution to a multivariable model for the prediction of UCB (odds ratio: 18.3; p<0.0001), which achieved a 90.8% predictive accuracy. Decision curve analysis revealed that models incorporating immunocytology achieved the highest net benefit at all threshold probabilities.
  
  
  CONCLUSIONS
  Immunocytology is a strong predictor of the presence of UCB in patients who present with painless hematuria. Incorporation of immunocytology into predictive models improves diagnostic accuracy by a statistically and clinically significant margin. The use of immunocytology in the diagnostic workup of patients with hematuria appears promising and should be further evaluated.
authors.affiliation: Department of Urology, Weill Cornell Medical College, New York-Presbyterian Hospital, New York, NY, USA.
authors.forename: Eugene K
authors.initials: EK
authors.lastname: Cha
authors.forename: Lenuta-Ancuta
authors.initials: LA
authors.lastname: Tirsar
authors.forename: Christian
authors.initials: C
authors.lastname: Schwentner
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Christos
authors.forename: Christine
authors.initials: C
authors.lastname: Mian
authors.forename: Joerg
authors.initials: J
authors.lastname: Hennenlotter
authors.forename: Thomas
authors.initials: T
authors.lastname: Martini
authors.forename: Arnulf
authors.initials: A
authors.lastname: Stenzl
authors.forename: Armin
authors.initials: A
authors.lastname: Pycha
authors.forename: Shahrokh F
authors.initials: SF
authors.lastname: Shariat
authors.forename: Bernd J
authors.initials: BJ
authors.lastname: Schmitz-Dräger
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D014408:Biomarkers, Tumor / Q000652:urine*; D001706:Biopsy; D003661:Decision Support Techniques; D005260:Female; D005455:Fluorescent Antibody Technique; D005858:Germany; D006417:Hematuria / Q000209:etiology*; D006801:Humans; D007558:Italy; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D049451:Nomograms; D016017:Odds Ratio; D011237:Predictive Value of Tests; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D012680:Sensitivity and Specificity; D016482:Urinalysis; D001749:Urinary Bladder Neoplasms / Q000150:complications / Q000175:diagnosis* / Q000276:immunology / Q000473:pathology / Q000652:urine; D019459:Urothelium / Q000276:immunology*; D055815:Young Adult
chemical_list: D014408:Biomarkers, Tumor