Document Detail

Adding renal scan data improves the accuracy of a computational model to predict vesicoureteral reflux resolution.
MedLine Citation:
PMID:  18715584     Owner:  NLM     Status:  MEDLINE    
PURPOSE: We previously developed a computational model to predict vesicoureteral reflux resolution 1 and 2 years after diagnosis. Previous studies suggest that an abnormal renal scan may be a predictor of the failure of vesicoureteral reflux to resolve. We investigated whether the addition of renal scan data would improve the accuracy of our computational model. MATERIALS AND METHODS: Medical records and renal scans were reviewed on 161 children, including 127 girls and 34 boys, with primary reflux between 1988 and 2004. In addition to the 9 input variables from our prior model, we added renal scan data on decreased relative renal function (40% or less in the refluxing kidney) and renal scars. Resolution outcome was evaluated 1 and 2 years after diagnosis. Data sets were prepared for 1 and 2-year outcomes, and randomized into a modeling set of 111 and a cross-validation set of 50. The model was constructed using neUROn++. RESULTS: A logistic regression model had the best fit with an ROC area of 0.945 for predicting reflux resolution in the 2-year model. This was improved compared to our previous model without renal scan data. A prognostic calculator using this model can be deployed for availability on the Internet, allowing input variables to be entered and calculating the odds of resolution. CONCLUSIONS: This computational model uses multiple variables, including renal scan data, to improve individualized prediction of early reflux resolution with almost 95% accuracy. The prognostic calculator is a useful tool for predicting individualized vesicoureteral reflux resolution.
Kenneth G Nepple; Matthew J Knudson; J Christopher Austin; Moshe Wald; Antoine A Makhlouf; Craig S Niederberger; Christopher S Cooper
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Publication Detail:
Type:  Journal Article     Date:  2008-08-20
Journal Detail:
Title:  The Journal of urology     Volume:  180     ISSN:  1527-3792     ISO Abbreviation:  J. Urol.     Publication Date:  2008 Oct 
Date Detail:
Created Date:  2008-09-12     Completed Date:  2008-10-27     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0376374     Medline TA:  J Urol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1648-52; discussion 1652     Citation Subset:  AIM; IM    
Division of Pediatric Urology, Department of Urology, University of Iowa, Iowa City, Iowa 52242-1089, USA.
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MeSH Terms
Cicatrix / radionuclide imaging
Decision Support Techniques*
Kidney / pathology,  radionuclide imaging*
Logistic Models*
ROC Curve
Retrospective Studies
Vesico-Ureteral Reflux / pathology,  therapy*

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