Adding Renal Scan Data Improves the Accuracy of a Computational Model to Predict Vesicoureteral Reflux Resolution

Kenneth G Nepple; Matthew J Knudson; J. Christopher Austin; Moshe Wald; Antoine A Makhlouf; Craig S Niederberger; Christopher S Cooper

doi:10.1016/j.juro.2008.03.109

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Adding Renal Scan Data Improves the Accuracy of a Computational Model to Predict Vesicoureteral Reflux Resolution

Journal article

Peer reviewed

Adding Renal Scan Data Improves the Accuracy of a Computational Model to Predict Vesicoureteral Reflux Resolution

Kenneth G Nepple, Matthew J Knudson, J. Christopher Austin, Moshe Wald, Antoine A Makhlouf, Craig S Niederberger and Christopher S Cooper

The Journal of urology, Vol.180(4), pp.1648-1652

2008

DOI: 10.1016/j.juro.2008.03.109

PMID: 18715584

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Abstract

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. 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++. 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. 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.

kidney

vesico-ureteral reflux

decision support techniques

radionuclide imaging

Details

Title: Subtitle: Adding Renal Scan Data Improves the Accuracy of a Computational Model to Predict Vesicoureteral Reflux Resolution
Creators: Kenneth G Nepple - Division of Pediatric Urology, Department of Urology, University of Iowa, Iowa City, Iowa
Matthew J Knudson - Division of Pediatric Urology, Department of Urology, University of Iowa, Iowa City, Iowa
J. Christopher Austin - Division of Pediatric Urology, Department of Urology, University of Iowa, Iowa City, Iowa
Moshe Wald - Division of Pediatric Urology, Department of Urology, University of Iowa, Iowa City, Iowa
Antoine A Makhlouf - Department of Urology, University of Minnesota, Minneapolis, Minnesota
Craig S Niederberger - Department of Urology, University of Illinois at Chicago, Chicago, Illinois
Christopher S Cooper - Division of Pediatric Urology, Department of Urology, University of Iowa, Iowa City, Iowa
Resource Type: Journal article
Publication Details: The Journal of urology, Vol.180(4), pp.1648-1652
Publisher: Elsevier Inc
DOI: 10.1016/j.juro.2008.03.109
PMID: 18715584
ISSN: 0022-5347
eISSN: 1527-3792
Language: English
Date published: 2008
Academic Unit: Stead Family Department of Pediatrics; Urology; Medicine Administration
Record Identifier: 9984051795102771

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