Predicting GFR after radical nephrectomy: the importance of split renal function

Purpose To evaluate a conceptually simple model to predict new-baseline-glomerular-filtration-rate (NBGFR) after radical nephrectomy (RN) based on split-renal-function (SRF) and renal-functional-compensation (RFC), and to compare its predictive accuracy against a validated non-SRF-based model. RN should only be considered when the tumor has increased oncologic potential and/or when there is concern about perioperative morbidity with PN due to increased tumor complexity. In these circumstances, accurate prediction of NBGFR after RN can be important, with a threshold NBGFR > 45 ml/min/1.73m 2 correlating with improved overall survival. Methods 236 RCC patients who underwent RN (2010–2012) with preoperative imaging (CT/MRI) and relevant functional data were included. NBGFR was defined as GFR 3–12 months post-RN. SRF was determined using semi-automated software that provides differential parenchymal-volume-analysis (PVA) from preoperative imaging. Our SRF-based model was: Predicted NBGFR = 1.24 (× Global GFR Pre-RN ) (× SRF Contralateral ), with 1.24 representing the mean RFC estimate from independent analyses. A non-SRF-based model was also assessed: Predicted NBGFR = 17 + preoperative GFR (× 0.65)–age (× 0.25) + 3 (if tumor > 7 cm)–2 (if diabetes). Alignment between predicted/observed NBGFR was assessed by comparing correlation coefficients and area-under-the-curve (AUC) analyses. Results The correlation-coefficients ( r ) were 0.87/0.72 for SRF-based/non-SRF-based models, respectively ( p = 0.005). For prediction of NBGFR > 45 ml/min/1.73m 2 , the SRF-based/non-SRF-based models provided AUC of 0.94/0.87, respectively ( p = 0.044). Conclusion Previous non-SRF-based models to predict NBGFR post-RN are complex and omit two important parameters: SRF and RFC. Our proposed model prioritizes these parameters and provides a conceptually simple, accurate, and clinically implementable approach to predict NBGFR post-RN. SRF can be easily obtained using PVA software that is affordable, readily available (FUJIFILM-Medical-Systems), and more accurate than nuclear-renal-scans. The SRF-based model demonstrates greater predictive-accuracy than a non-SRF-based model, including the clinically-important predictive-threshold of NBGFR > 45 ml/min/1.73m 2 .