| Adding renal scan data improves the accuracy of a computational model to predict vesicoureteral reflux resolution. | |
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MedLine Citation:
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PMID: 18715584 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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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. |
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Authors:
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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:
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Type: Journal Article Date: 2008-08-20 |
Journal Detail:
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Title: The Journal of urology Volume: 180 ISSN: 1527-3792 ISO Abbreviation: J. Urol. Publication Date: 2008 Oct |
Date Detail:
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Created Date: 2008-09-12 Completed Date: 2008-10-27 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0376374 Medline TA: J Urol Country: United States |
Other Details:
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Languages: eng Pagination: 1648-52; discussion 1652 Citation Subset: AIM; IM |
Affiliation:
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Division of Pediatric Urology, Department of Urology, University of Iowa, Iowa City, Iowa 52242-1089, USA. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Cicatrix
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radionuclide imaging Decision Support Techniques* Humans Kidney / pathology, radionuclide imaging* Logistic Models* ROC Curve Retrospective Studies Vesico-Ureteral Reflux / pathology, therapy* |
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