[en] [en] BACKGROUND AND HYPOTHESIS: The estimation of glomerular filtration rate (GFR) is one main tool to detect renal disease. The most used biomarker remains serum creatinine and the European Kidney Function Consortium (EKFCcrea) equation is the most validated in Europe. More recently, cystatin C, has been proposed. We studied the performances of the EKFC equations in a large cohort of subjects according to their diabetic status.
METHODS: Four cohorts from the EKFC dataset were retrospectively considered in which the diabetic status was available. GFR was measured by plasma clearances (mGFR) (iohexol or 51Cr-EDTA). The performance of the equations was assessed by calculating bias, precision (IQR) and P30 (percentage of eGFR-values within ± 30% of mGFR).
RESULTS: In the whole population (n = 6 158), median [IQR] age was 61 [47;72] years, with 45.8% women. Mean mGFR was 60 [39;82] mL/min/1.73m². Compared to non-diabetic individuals (n = 5 124), diabetic patients (n = 1 034) were older, more frequently male, heavier, and had lower mGFR. The performance of the EKFCcys equation was similar to EKFCcrea, but the EKFCcrea+cys had better P30 than the single-biomarker equations. P30 values were substantially lower in diabetic patients than in non-diabetic but, according to a matched analysis, this is mainly explained by the difference in GFR levels between the two populations, not by diabetic status.
CONCLUSION: We showed that equation combining creatinine and cystatin C present a better performance. If accuracy of equations seems better in non-diabetic than in diabetic individuals, it is more due to differences in GFR levels than to the diabetic status.
Disciplines :
Urology & nephrology
Author, co-author :
Delanaye, Pierre ; Université de Liège - ULiège > Département des sciences cliniques ; Department of Nephrology-Dialysis-Apheresis, Hôpital Universitaire Carémeau, Nîmes, France
Björk, Jonas ; Division of Occupational and Environmental Medicine, Lund University, Lund, Sweden ; Clinical Studies Sweden, Forum South, Skåne University Hospital, Lund, Sweden
Vidal-Petiot, Emmanuelle ; Assistance Publique-Hôpitaux de Paris, Bichat Hospital, and Université de Paris, UMR S1138, Cordeliers Research Center, Paris, France
Flamant, Martin; Assistance Publique-Hôpitaux de Paris, Bichat Hospital, and Université de Paris, UMR S1138, Cordeliers Research Center, Paris, France
Ebert, Natalie ; Charité Universitätsmedizin Berlin, Institute of Public Health, Berlin, Germany
Schaeffner, Elke; Charité Universitätsmedizin Berlin, Institute of Public Health, Berlin, Germany
Grubb, Anders ; Department of Clinical Chemistry, Skåne University Hospital, Lund, Lund University, Sweden
Christensson, Anders ; Department of Nephrology, Skåne University Hospital, Lund University, Malmö, Sweden
Nyman, Ulf; Department of Translational Medicine, Division of Medical Radiology, Lund University, Malmö, Sweden
Stehlé, Thomas ; Université Paris Est Créteil, INSERM, Institut Mondor de Recherche Biomédicale (IMRB), Créteil, France ; Assistance Publique-Hôpitaux de Paris, Hôpitaux Universitaires Henri Mondor, Service de Néphrologie et Transplantation, Fédération Hospitalo-Universitaire « Innovative therapy for immune disorders », Créteil, France
Pottel, Hans ; Université de Liège - ULiège > Département des sciences cliniques ; Department of Public Health and Primary Care, KU Leuven Campus Kulak Kortrijk, Kortrijk, Belgium
Language :
English
Title :
Diabetic status and the performances of creatinine- and cystatin C-based eGFR equations.
Kidney Disease: Improving Global Outcomes Diabetes Work Group. KDIGO 2022 clinical practice guideline for diabetes management in chronic kidney disease. Kidney Int 2022; 102 (5 Suppl):S1-127. https://doi.org/10.1016/j.kint.2022.06.008
Kidney Disease: Improving Global Outcomes CKD Work Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl 2013; 3 :1-150.
Delanaye P, Cavalier E, Pottel H. Serum creatinine: not so simple! Nephron 2017; 136 :302-8.
Delanaye P, Cavalier E, Pottel H et al. New and old GFR equations: a European perspective. Clin Kidney J 2023; 16 :1375-83. https://doi.org/10.1093/ckj/sfad039
Inker LA, Eneanya ND, Coresh J et al. New creatinine- and cys- tatin C-based equations to estimate GFR without race. N Engl J Med 2021; 385 :1737-49. https://doi.org/10.1056/NEJMoa2102953
Nyman U, Grubb A, Larsson A et al. The revised Lund-MalmöGFR estimating equation outperforms MDRD and CKD-EPI across GFR, age and BMI intervals in a large Swedish popula- tion. Clin Chem Lab Med 2014; 52 :815-24. https://doi.org/10.1515/cclm-2013-0741
Pottel H, Björk J, Courbebaisse M et al. Development and valida- tion of a modified full age spectrum creatinine-based equation to estimate glomerular filtration rate: a cross-sectional analysis of pooled data. Ann Intern Med 2021; 174 :183-91. https://doi.org/10.7326/M20-4366
Delanaye P, Vidal-Petiot E, Björk J et al. Performance of creatinine-based equations to estimate glomerular filtration rate in White and Black populations in Europe, Brazil, and Africa. Nephrol Dial Transplant 2023; 38 :106-18. https://doi.org/10.1093/ndt/gfac241
Delanaye P, Rule AD, Schaeffner ES et al. Performance of the European Kidney Function Consortium (EKFC) creatinine-based equation in American cohorts. Kidney Int 2024; 105 :629-37. https://doi.org/10.1016/j.kint.2023.11.024
Delanaye P, Pottel H. Estimating glomerular filtration rate in China: is the European Kidney Function Consortium (EKFC) equation the solution? Nephron 2024; 148 :74-7. https://doi.org/10.1159/000531314
Malmgren L, Öberg C, den Bakker E et al. The complexity of kid- ney disease and diagnosing it -cystatin C, selective glomerular hypofiltration syndromes and proteome regulation. J Intern Med 2023; 293 :293-308. https://doi.org/10.1111/joim.13589
Pottel H, Björk J, Rule AD et al. Cystatin C-based equation to es- timate GFR without the inclusion of race and sex. N Engl J Med 2023; 388 :333-43. https://doi.org/10.1056/NEJMoa2203769
Grubb A, Horio M, Hansson LO et al. Generation of a new cys- tatin C-based estimating equation for glomerular filtration rate by use of 7 assays standardized to the international calibra- tor. Clin Chem 2014; 60 :974-86. https://doi.org/10.1373/clinchem. 2013.220707
Jiao Y, Jiang S, Zhou J et al. Diabetes influences the performance of creatinine-based equations for estimating glomerular filtra- tion rate in the elderly population. Eur J Intern Med 2022; 100 : 146-8. https://doi.org/10.1016/j.ejim.2022.02.018
Camargo EG, Soares AA, Detanico AB et al. The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation is less accurate in patients with type 2 diabetes when compared with healthy individuals. Diabet Med 2011; 28 :90-5. https://doi.org/10. 1111/j.1464-5491.2010.03161.x
Zafari N, Churilov L, Wong LYL et al. Evaluation of the diag- nostic performance of the creatinine-based Chronic Kidney Dis- ease Epidemiology Collaboration equation in people with dia- betes: a systematic review. Diabet Med 2021; 38 :e14391. https://doi.org/10.1111/dme.14391
Fan L, Inker LA, Rossert J et al. Glomerular filtration rate es- timation using cystatin C alone or combined with creatinine as a confirmatory test. Nephrol Dial Transplant 2014; 29 :1195-203. https://doi.org/10.1093/ndt/gft509
Rognant N, Lemoine S, Laville M et al. Performance of the chronic kidney disease epidemiology collaboration equation to esti- mate glomerular filtration rate in diabetic patients. Diabetes Care 2011; 34 :1320-2. https://doi.org/10.2337/dc11-0203
Silveiro SP, Araújo GN, Ferreira MN et al. Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation pronouncedly underestimates glomerular filtration rate in type 2 diabetes. Diabetes Care 2011; 34 :2353-5. https://doi.org/10.2337/dc11-1282
Maple-Brown LJ, Ekinci EI, Hughes JT et al. Performance of formu- las for estimating glomerular filtration rate in Indigenous Aus- tralians with and without type 2 diabetes: the eGFR Study. Diabet Med 2014; 31 :829-38. https://doi.org/10.1111/dme.12426
Wood AJ, Churilov L, Perera N et al. Estimating glomerular fil- tration rate: performance of the CKD-EPI equation over time in patients with type 2 diabetes. J Diabetes Complications 2016; 30 : 49-54. https://doi.org/10.1016/j.jdiacomp.2015.08.025
Liu X, Qiu X, Shi C et al. Modified glomerular filtration rate-estimating equations developed in Asiatic population for Chinese patients with type 2 diabetes. Int J Endocrinol 2014; 2014 :521071. https://doi.org/10.1155/2014/521071
Cheuiche AV, Queiroz M, Azeredo-da-Silva ALF et al. Perfor- mance of cystatin C-based equations for estimation of glomeru- lar filtration rate in diabetes patients: a Prisma-compliant systematic review and meta-analysis. Sci Rep 2019; 9 :1418. https://doi.org/10.1038/s41598-018-38286-9
Macisaac RJ, Tsalamandris C, Thomas MC et al. Estimating glomerular filtration rate in diabetes: a comparison of cystatin- C- and creatinine-based methods. Diabetologia 2006; 49 :1686-9. https://doi.org/10.1007/s00125-006-0275-7
Rigalleau V, Beauvieux MC, Le Moigne F et al. Cystatin C im- proves the diagnosis and stratification of chronic kidney disease, and the estimation of glomerular filtration rate in diabetes. Dia- betes Metab 2008; 34 :482-9. https://doi.org/10.1016/j.diabet.2008. 03.004
Beauvieux MC, Le Moigne F, Lasseur C et al. New predictive equa- tions improve monitoring of kidney function in patients with diabetes. Diabetes Care 2007; 30 :1988-94. https://doi.org/10.2337/dc06-2637
Tsai C-W, Grams ME, Inker LA et al. Cystatin C- and creatinine- based estimated glomerular filtration rate, vascular disease, and mortality in persons with diabetes in the U.S. Diabetes Care 2014; 37 :1002-8. https://doi.org/10.2337/dc13-1910
Inker LA, Schmid CH, Tighiouart H et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med 2012; 367 :20-9. https://doi.org/10.1056/NEJMoa1114248
Fu EL, Levey AS, Coresh J et al. Accuracy of GFR estimating equa- tions in patients with discordances between creatinine and cys- tatin C-based estimations. J Am Soc Nephrol 2023; 34 :1241-51. https://doi.org/10.1681/ASN.0000000000000128
Schaeffner ES, Ebert N, Delanaye P et al. Two novel equa- tions to estimate kidney function in persons aged 70 years or older. Ann Intern Med 2012; 157 :471-81. https://doi.org/10.7326/0003-4819-157-7-201210020-00003
Delanaye P, Flamant M, Dubourg L et al. Single- versus multiple-sample method to measure glomerular filtration rate. Nephrol Dial Transplant 2018; 33 :1778-85. https://doi.org/10.1093/ndt/gfx345
Brandstrom E, Grzegorczyk A, Jacobsson L et al. GFR mea- surement with iohexol and 51Cr-EDTA. A comparison of the two favoured GFR markers in Europe. Nephrol Dial Transplant 1998; 13 :1176-82. https://doi.org/10.1093/ndt/13.5.1176
Ebert N, Jakob O, Gaedeke J et al. Prevalence of reduced kidney function and albuminuria in older adults: the Berlin Initiative Study. Nephrol Dial Transplant 2017; 32 :997-1005.
Nyman U, Björk J, Delanaye P et al. Rescaling creatinine makes GFR estimation equations generally applicable across populations-validation results for the Lund-Malmöequation in a French cohort of sub-Saharan ancestry. Clin Chem Lab Med 2024; 62 :421-7. https://doi.org/10.1515/cclm-2023-0496
Delanaye P, Pottel H, Botev R. Con: Should we abandon the use of the MDRD equation in favour of the CKD-EPI equa- tion? Nephrol Dial Transplant 2013; 28 :1396-403. https://doi.org/10.1093/ndt/gft006
National Kidney Foundation. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and strat- ification. Am J Kidney Dis 2002; 39 (2 Suppl 1):S1-266.
Mortensen LQ, Andresen K, Burcharth J et al. Matching cases and controls using SAS®software. Front Big Data 2019; 2 :4. https://doi. org/10.3389/fdata.2019.00004
Gaspari F, Ruggenenti P, Porrini E et al. The GFR and GFR decline cannot be accurately estimated in type 2 diabetics. Kidney Int 2013; 84 :164-73. https://doi.org/10.1038/ki.2013.47
Delanaye P, Dubourg L, Flamant M et al. Comparison of early- compartment correction equations for glomerular filtration rate measurements. Kidney Int Rep 2020; 5 :1079-81. https://doi.org/10. 1016/j.ekir.2020.04.015
Delanaye P, Vidal-Petiot E, StehléTetal. Comparisonofplasma clearance with early-compartment correction equations and urinary clearance in high glomerular filtration rate. Kidney Int Rep 2021; 6 :1622-8. https://doi.org/10.1016/j.ekir.2021.03.886