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Validation of a mathematical model to predict renal function after nephron sparing surgery

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Sources of Funding: none

Introduction

Several nephrometry scores have been published in recent years for the purpose of standardizing the anatomy of renal tumors. The most common is the RENAL nephrometry score (NS) that has been associated with peri-operative outcomes. The association of NS with post-operative renal function is still unclear. Recently the concept of Contact Surface Area (CSA) has been introduced and shown to correlate with post-operative renal function. Our aim was to validate CSA as a predictive tool for renal function after nephron sparing surgery (NSS).

Methods

The study included all patients who were diagnosed with renal cell carcinoma and underwent NSS at our institute between 1998 and 2014. Patients without renal function, adequate cross sectional imaging or NS information were excluded. CSA was calculated based on abdominal computerized tomography or magnetic resonance imaging using the formula developed by Hsieh et al (The Journal of urology;196(1):33-40). eGFR was calculated using the most recent pre-operative and last follow-up creatinine. The correlation between CSA and NS, absolute and percent change in eGFR (ACE and PCE respectively) was examined by spearman correlation coefficient (SCC). Linear regression model was fitted to examine the association of NS and CSA with ACE and PCE. ROC curve analysis was performed to examine CSA and NS ability to predict more than 10% loss in renal function.

Results

234 patients underwent NSS and had sufficient renal function, NS information and adequate imaging to assess CSA (all between 2005-2014). Mean (SD) CSA was 35.3 (52.1) cm2 and median (IQR) NS was 9 (7-10). Median follow-up was 55 months (IQR 37-78). CSA was significantly correlated with NS (SCC 0.727, p<0.001). Furthermore, CSA was significantly correlated with ACE and PCE (SCC -0.97 and -0.95 respectively, p<0.001). Both CSA and RS independently affected change in renal function on multivariable analysis (p<0.001). However, CSA better predicted 10% renal function decline compared with NS on ROC curve analysis (figure, AUC 0.93 vs 0.83).

Conclusions

CSA is significantly correlated with NS. Both CSA and NS are significantly correlated with renal function change after NSS. However, CSA is a better predictor of renal function decline compared to RS._x000D_

Funding

none

Authors
Miki Haifler
Andrew Higgins
Benjamin Ristau
Andres Correa
shreyas Joshi
Richard Greenberg
David Chen
Alexander Kutikov
Rosalia Viterbo
Amnon Zisman
Robert Uzzo
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