title: Decision curve analysis assessing the clinical benefit of NMP22 in the detection of bladder cancer: secondary analysis of a prospective trial.
abstract: OBJECTIVE
  • To employ decision curve analysis to determine the impact of nuclear matrix protein 22 (NMP22) on clinical decision making in the detection of bladder cancer using data from a prospective trial.
  
  
  METHODS
  • The study included 1303 patients at risk for bladder cancer who underwent cystoscopy, urine cytology and measurement of urinary NMP22 levels. • We constructed several prediction models to estimate risk of bladder cancer. The base model was generated using patient characteristics (age, gender, race, smoking and haematuria); cytology and NMP22 were added to the base model to determine effects on predictive accuracy. • Clinical net benefit was calculated by summing the benefits and subtracting the harms and weighting these by the threshold probability at which a patient or clinician would opt for cystoscopy.
  
  
  RESULTS
  • In all, 72 patients were found to have bladder cancer (5.5%). In univariate analyses, NMP22 was the strongest predictor of bladder cancer presence (predictive accuracy 71.3%), followed by age (67.5%) and cytology (64.3%). • In multivariable prediction models, NMP22 improved the predictive accuracy of the base model by 8.2% (area under the curve 70.2-78.4%) and of the base model plus cytology by 4.2% (area under the curve 75.9-80.1%). • Decision curve analysis revealed that adding NMP22 to other models increased clinical benefit, particularly at higher threshold probabilities.
  
  
  CONCLUSIONS
  • NMP22 is a strong, independent predictor of bladder cancer. • Addition of NMP22 improves the accuracy of standard predictors by a statistically and clinically significant margin. • Decision curve analysis suggests that integration of NMP22 into clinical decision making helps avoid unnecessary cystoscopies, with minimal increased risk of missing a cancer.
authors.affiliation: Department of Urology, Weill Medical College of Cornell University, New York-Presbyterian Hospital, New York, NY 10065, USA.
authors.forename: Christopher E
authors.initials: CE
authors.lastname: Barbieri
authors.forename: Eugene K
authors.initials: EK
authors.lastname: Cha
authors.forename: Thomas F
authors.initials: TF
authors.lastname: Chromecki
authors.forename: Allison
authors.initials: A
authors.lastname: Dunning
authors.forename: Yair
authors.initials: Y
authors.lastname: Lotan
authors.forename: Robert S
authors.initials: RS
authors.lastname: Svatek
authors.forename: Douglas S
authors.initials: DS
authors.lastname: Scherr
authors.forename: Pierre I
authors.initials: PI
authors.lastname: Karakiewicz
authors.forename: Maxine
authors.initials: M
authors.lastname: Sun
authors.forename: Madhu
authors.initials: M
authors.lastname: Mazumdar
authors.forename: Shahrokh F
authors.initials: SF
authors.lastname: Shariat
mesh_terms: D000368:Aged; D002295:Carcinoma, Transitional Cell / Q000175:diagnosis* / Q000652:urine*; D002986:Clinical Trials as Topic; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009687:Nuclear Proteins / Q000652:urine*; D011446:Prospective Studies; D012189:Retrospective Studies; D001749:Urinary Bladder Neoplasms / Q000175:diagnosis* / Q000652:urine*
chemical_list: D009687:Nuclear Proteins; C100379:nuclear matrix protein 22