Department of Urology Division of Medical Oncology Division of Biostatistics and Epidemiology, Weill Medical College of Cornell University, New York-Presbyterian Hospital, New York, NY.
Department of Urology, University of Texas Southwestern Medical Center, Dallas, TX; Department of Urology, University of Texas Health Science Center, San Antonio, TX, USA; Cancer Prognostics and Health Outcome Unit, University of Montreal Health Center, Montreal, Quebec, Canada.
Study Type - Decision analysis (based on alternative scenarios) Level of Evidence 2b.
What's known on the subject? and What does the study add? Several studies have shown that abnormal levels of nuclear matrix protein 22 (NMP22) are associated with bladder cancer, and NMP22 has been approved by the FDA as a urinary biomarker for bladder cancer detection and surveillance. However, the benefit of adding NMP22 to the clinical care of patients remains unclear. Decision curve analysis incorporates the consequences of clinical decisions, such as an increased number of unnecessary cystoscopies or missed cancers.
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.
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.
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.
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.
Written by:
Barbieri CE, Cha EK, Chromecki TF, Dunning A, Lotan Y, Svatek RS, Scherr DS, Karakiewicz PI, Sun M, Mazumdar M, Shariat SF. Are you the author?
Reference: BJU Int. 2011 Aug 18. Epub ahead of print.
doi: 10.1111/j.1464-410X.2011.010419.x
PubMed Abstract
PMID: 21851550
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