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Erschienen in:

12.01.2022 | Original Article

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

verfasst von: Nityam Rathi, Diego A. Palacios, Emily Abramczyk, Hajime Tanaka, Yunlin Ye, Jianbo Li, Yosuke Yasuda, Robert Abouassaly, Mohamed Eltemamy, Alvin Wee, Christopher Weight, Steven C. Campbell

Erschienen in: World Journal of Urology | Ausgabe 4/2022

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Abstract

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/1.73m² 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/1.73m², 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/1.73m².

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Titel: Predicting GFR after radical nephrectomy: the importance of split renal function
verfasst von: Nityam Rathi
Diego A. Palacios
Emily Abramczyk
Hajime Tanaka
Yunlin Ye
Jianbo Li
Yosuke Yasuda
Robert Abouassaly
Mohamed Eltemamy
Alvin Wee
Christopher Weight
Steven C. Campbell
Publikationsdatum: 12.01.2022
Verlag: Springer Berlin Heidelberg
Erschienen in: World Journal of Urology / Ausgabe 4/2022
Print ISSN: 0724-4983
Elektronische ISSN: 1433-8726
DOI: https://doi.org/10.1007/s00345-021-03918-9

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