Optimizing prediction of new-baseline glomerular filtration rate after radical nephrectomy: are algorithms really necessary?

Algorithms Carcinoma, Renal Cell / diagnostic imaging Glomerular Filtration Rate Humans Kidney / diagnostic imaging Kidney Neoplasms / pathology Nephrectomy / methods Retrospective Studies
Functional compensation Kidney cancer Parenchymal volume analysis Radical nephrectomy Split renal function

Journal

International urology and nephrology
ISSN: 1573-2584
Titre abrégé: Int Urol Nephrol
Pays: Netherlands
ID NLM: 0262521

Informations de publication

Date de publication:
Oct 2022
Historique:
received: 08 05 2022
accepted: 04 07 2022
pubmed: 18 7 2022
medline: 14 9 2022
entrez: 17 7 2022
Statut: ppublish

Résumé

Radical nephrectomy (RN) is an important consideration for the management of localized renal-cell-carcinoma (RCC) whenever the tumor appears aggressive, although reduced renal function is a concern. Split-renal-function (SRF) in the contralateral kidney and postoperative renal functional compensation (RFC) are fundamentally important for the accurate prediction of new baseline GFR (NBGFR) post-RN. SRF can be estimated either from nuclear renal scans (NRS) or from preoperative imaging using parenchymal-volume-analysis (PVA). We compare two SRF-based models for predicting NBGFR after RN with a subjective prediction of NBGFR by an experienced urologic-oncologist. 187 RCC patients managed with RN (2006-16) were included based on the availability of preoperative CT/MRI and NRS, and preoperative/postoperative eGFR. NBGFR was defined as the final GFR 3-12 months post-RN. For the SRF-based approaches, SRF was derived from either NRS or PVA, and RFC was estimated at 25% based on previous independent analyses. Thus, the formula (Global GFR The r values for subjective-assessment, NRS/SRF-based, and PVA/SRF-based approaches were 0.72/0.72/0.85, respectively (p < 0.05). The PVA/SRF-based model also demonstrated significant improvement across other performance parameters. The PVA/SRF-based model more accurately predicts NBGFR post-RN than NRS/SRF-based and Subjective Estimation. PVA software (Fujifilm-medical-systems) is readily available and affordable and provides accurate SRF estimations from routine preoperative imaging. This novel approach may inform clinical management regarding RN/PN for complex RCC cases.

Identifiants

DOI: 10.1007/s11255-022-03298-y PMID: 35842890
pubmed: 35842890
doi: 10.1007/s11255-022-03298-y
pii: 10.1007/s11255-022-03298-y
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2537-2545

Informations de copyright

© 2022. The Author(s), under exclusive licence to Springer Nature B.V.

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Auteurs

Nityam Rathi (N)

Center for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.

Yosuke Yasuda (Y)

Center for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.
Department of Urology, Tokyo Medical and Dental University, Tokyo, Japan.

Worapat Attawettayanon (W)

Center for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.
Division of Urology, Department of Surgery, Faculty of Medicine, Songklanagarind Hospital, Prince of Songkla University, Songkhla, Thailand.

Diego A Palacios (DA)

Center for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.

Yunlin Ye (Y)

Center for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.
Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.

Jianbo Li (J)

Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA.

Christopher Weight (C)

Center for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.

Mohammed Eltemamy (M)

Center for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.

Tarik Benidir (T)

Center for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.

Robert Abouassaly (R)

Center for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA.

Steven C Campbell (SC)

Center for Urologic Oncology, Glickman Urological and Kidney Institute, Room Q10-120, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH, USA. campbes3@ccf.org.

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Classifications MeSH

questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Algorithmes › Optimizing prediction of new-baseline...
questionsmedicales.fr › Maladies urogénitales › Maladies urologiques › Tumeurs urologiques › Tumeurs du rein › Néphrocarcinome › Optimizing prediction of new-baseline...
questionsmedicales.fr › Phénomènes physiologiques des appareils urinaire et reproducteur › Phénomènes physiologiques des voies urinaires › Débit de filtration glomérulaire › Optimizing prediction of new-baseline...
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questionsmedicales.fr › Maladies urogénitales › Maladies urologiques › Tumeurs urologiques › Tumeurs du rein › Optimizing prediction of new-baseline...
questionsmedicales.fr › Procédures de chirurgie opératoire › Procédures de chirurgie urogénitale › Procédures de chirurgie urologique › Néphrectomie › Optimizing prediction of new-baseline...
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