[en] [en] INTRODUCTION: Discordant results between cystatin C and creatinine in estimating glomerular filtration rate (GFR) are an important medical issue. However, the equation that should be used when GFR estimates are discordant remains unclear.
METHODS: This cross-sectional analysis included 15,485 participants with GFR measured by the clearance of an exogenous marker, serum creatinine, and cystatin C. We studied the proportion of discordant results defined as an absolute (> 15 ml/min per 1.73 m2) or relative (> 20%) difference between creatinine-based estimated GFR (eGFR, eGFRcrea) and cystatin C-based eGFR (eGFRcys) using different equations (Chronic Kidney Disease Epidemiology Collaboration [CKD-EPI], European Kidney Function Consortium [EKFC], and reexpressed Lund-Malmö [r-LMR]). We also researched for the best estimating equations to be used in subjects with concordant or discordant results to estimate measured GFR (mGFR).
RESULTS: In the total cohort, the proportion of subjects with discordant results (absolute or relative) was larger for CKD-EPI (35.1 and 40.6%) than for EKFC (21.9 and 31.7%) or r-LMR (22.8 and 32.8%) equations. Among discrepant results, the proportion of eGFRcys < eGFRcrea was significantly higher than the proportion of eGFRcrea < eGFRcys for the CKD-EPI equations, whereas the occurrence of discrepancy was similar in the 2 discrepant groups for EKFC or r-LMR. For the EKFC and r-LMR equations, but not for the CKD-EPI, the equation combining creatinine and cystatin C was consistently the closest to the mGFR in the discrepant groups.
CONCLUSION: Based on the lower discrepancy proportion, better balance between eGFRcrea and eGFRcys, and better concordance with mGFR, the EKFC, and r-LMR equations should be preferred over the CKD-EPI to estimate GFR.
Disciplines :
Urology & nephrology
Author, co-author :
Delanaye, Pierre ; Université de Liège - ULiège > Département des sciences cliniques > Néphrologie ; Department of Nephrology-Dialysis-Apheresis, Hôpital Universitaire Carémeau, Université de Montpellier, Nîmes, France
Flamant, Martin; Assistance Publique-Hôpitaux de Paris, Bichat Hospital, INSERM U1148, Université Paris Cité and Université Sorbonne Paris Nord, LVTS, Center, Paris, France
Vidal-Petiot, Emmanuelle; Assistance Publique-Hôpitaux de Paris, Bichat Hospital, INSERM U1148, Université Paris Cité and Université Sorbonne Paris Nord, LVTS, Center, Paris, France
Björk, Jonas; Division of Occupational and Environmental Medicine, Lund University, Lund, Sweden ; Clinical Studies Sweden, Forum South, Skåne University Hospital, Lund, Sweden
Nyman, Ulf; Department of Translational Medicine, Division of Medical Radiology, Lund University, Malmö, Sweden
Grubb, Anders; Department of Clinical Chemistry, Skåne University Hospital, Lund University, Lund, Sweden
Bakker, Stephan J L; Division of Nephrology, Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
de Borst, Martin H; Division of Nephrology, Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
van Londen, Marco; Division of Nephrology, Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
Derain-Dubourg, Laurence; Néphrologie, Dialyse, Hypertension et Exploration Fonctionnelle Rénale, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
Rule, Andrew D; Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA
Eriksen, Björn O; Section of Nephrology, University Hospital of North Norway and Metabolic and Renal Research Group, UiT The Arctic University of Norway, Tromsø, Norway
Melsom, Toralf; Section of Nephrology, University Hospital of North Norway and Metabolic and Renal Research Group, UiT The Arctic University of Norway, Tromsø, Norway
Sundin, Per-Ola; Karla Healthcare Centre, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
Ebert, Natalie; Charité Universitätsmedizin Berlin, Institute of Public Health, Berlin, Germany
Schaeffner, Elke; Charité Universitätsmedizin Berlin, Institute of Public Health, Berlin, Germany
Hansson, Magnus; Function Area Clinical Chemistry, Karolinska University Laboratory, Department of Laboratory Medicine, Karolinska University Hospital Huddinge, Karolinska Institute, Stockholm, Sweden
Littmann, Karin; Division of Medicine Huddinge (MedH), Karolinska Institute, Stockholm, Sweden
Larsson, Anders; Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden
Stehlé, Thomas; Université Paris Est Créteil, INSERM, Institut Mondor de Recherche Biomédicale, 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
Cavalier, Etienne ; Université de Liège - ULiège > Département de pharmacie > Chimie médicale
Bukabau, Justine B; Renal Unit, Department of Internal Medicine, Kinshasa University Hospital, University of Kinshasa, Kinshasa, Democratic Republic of the Congo
Sumaili, Ernest K; Renal Unit, Department of Internal Medicine, Kinshasa University Hospital, University of Kinshasa, Kinshasa, Democratic Republic of the Congo
Yayo, Eric; Département de Biochimie, UFR Sciences Pharmaceutiques et Biologiques, Université Felix Houphouët Boigny, Abidjan, Côte d'Ivoire
Mariat, Christophe; Service de Néphrologie, Dialyse et Transplantation Rénale, Hôpital Nord, CHU de Saint-Etienne, France
Moranne, Olivier; Department of Nephrology-Dialysis-Apheresis, Hôpital Universitaire Carémeau, Université de Montpellier, Nîmes, France
Christensson, Anders; Department of Nephrology, Skåne University Hospital, Lund University, Malmö, Sweden
Lanot, Antoine; Normandie Université, Unicaen, CHU de Caen Normandie, Néphrologie, Côte de Nacre Caen, France ; Normandie Université, Unicaen, UFR de médecine, Caen, France ; ANTICIPE" U1086 INSERM-UCN, Center François Baclesse, Caen, France ; Department of Public Health and Primary Care, KU Leuven Campus Kulak Kortrijk, Kortrijk, Belgium
Pottel, Hans ; Université de Liège - ULiège > Département des sciences cliniques ; Department of Public Health and Primary Care, KU Leuven Campus Kulak Kortrijk, Kortrijk, Belgium
We Thank Edmund J. Lamb from the Department of Clinical Biochemistry, East Kent Hospitals University NHS Foundation Trust, Canterbury, United Kingdom for sharing his data. The results presented in this paper have not been previously published, either in whole or in part. Swedish Research Council (Vetenskapsr\u00E5det; grant no. 2019-00198). Professor J. Bj\u00F6rk received funding from the Swedish Research Council (VR) to conduct large-scale epidemiological studies linked with registered healthcare data. This funding source was not involved in the design, analysis, presentation, or interpretation of the study results. A short protocol is available to interested readers by contacting PD at pdelanaye@chuliege.be. SAS code is available to interested readers by contacting HP at hans.pottel@kuleuven.be. The EKFC dataset used in the present study is hosted by the Lund University Population Research Platform. Legal and ethical restrictions prevent public sharing of datasets. Data can be made available for collaborations upon request of interested researchers but would generally require new ethical permission and permission from each of the data owners. You can find contact information for the data host at https://www.lupop.lu.se/. The GENOA/ECAC, Paris, Cr\u00E9teil, N\u00EEmes and Groningen data are not publicly available because of the confidential nature of patient information obtained for clinical care. Legal and ethical restrictions prevent public sharing of datasets. Data can be made available for collaborations upon request of interested researchers but would generally require new ethical permission and permission from each of the data owners.Swedish Research Council (Vetenskapsr\u00E5det; grant no. 2019 \u2013 00198). Professor J. Bj\u00F6rk has funding from the Swedish Research Council (VR) in order to conduct large scale epidemiological studies linked with registered data from health care. This funding source was not at all involved in design, analysis, presentation or interpretation of the results from the present study.
Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2024 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl 105 (2024), S117–S314.
Pottel, H., Björk, J., Rule, A.D., et al. Cystatin C–based equation to estimate GFR without the inclusion of race and sex. N Engl J Med 388 (2023), 333–343, 10.1056/NEJMoa2203769.
Inker, L.A., Schmid, C.H., Tighiouart, H., et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med 367 (2012), 20–29, 10.1056/NEJMoa1114248.
Carrero, J.J., Fu, E.L., Sang, Y., et al. Discordances between creatinine and cystatin C-based estimated GFR and adverse clinical outcomes in routine clinical practice. Am J Kidney Dis 82 (2023), 534–542, 10.1053/j.ajkd.2023.04.002.
Chen, D.C., Lu, K., Scherzer, R., et al. Cystatin C- and creatinine-based estimated GFR differences: Prevalence and predictors in the UK Biobank. Kidney Med, 6, 2024, 100796, 10.1016/j.xkme.2024.100796.
Fu, E.L., Levey, A.S., Coresh, J., et al. Accuracy of GFR estimating equations in patients with discordances between creatinine and cystatin C-based estimations. J Am Soc Nephrol 34 (2023), 1241–1251, 10.1681/ASN.0000000000000128.
Potok, O.A., Rifkin, D.E., Ix, J.H., et al. Estimated GFR accuracy when cystatin C and creatinine-based estimates are discrepant in older adults. Kidney Med, 5, 2023, 100628, 10.1016/j.xkme.2023.100628.
Wang, Y., Adingwupu, O.M., Shlipak, M.G., et al. Discordance between creatinine-based and cystatin C–based estimated GFR: Interpretation according to performance compared to measured GFR. Kidney Med, 5, 2023, 100710, 10.1016/j.xkme.2023.100710.
Björk, J., Grubb, A., Larsson, A., et al. Accuracy of GFR estimating equations combining standardized cystatin C and creatinine assays: A cross-sectional study in Sweden. Clin Chem Lab Med 53 (2015), 403–414, 10.1515/cclm-2014-0578.
Åkesson, A., Lindström, V., Nyman, U., et al. Shrunken pore syndrome and mortality: A cohort study of patients with measured GFR and known comorbidities. Scand J Clin Lab Investig 80 (2020), 412–422, 10.1080/00365513.2020.1759139.
Rule, A.D., Glassock, R.J., Cystatin C and the misdiagnosis of CKD in older adults. Nat Rev Nephrol 6 (2024), 560–561, 10.1038/s41581-024-00852-y.
Fu, E.L., Carrero, J.J., Sang, Y., et al. Association of low glomerular filtration rate with adverse outcomes at older age in a large population with routinely measured cystatin C. Ann Intern Med Med 177 (2024), 269–279, 10.7326/M23-1138.
Malmgren, L., Öberg, C., den Bakker, E., et al. The complexity of kidney disease and diagnosing it – cystatin C, selective glomerular hypofiltration syndromes and proteome regulation. J Intern Med 293 (2023), 293–308, 10.1111/joim.13589.
Farrington, D., Surapaneni, A., Matsushita, K., Seegmiller, J.C., Coresh, J., Grams, M., Discrepancies between cystatin C-based and creatinine-based estimated glomerular filtration rates. Clin J Am Soc Nephrol 18 (2023), 1143–1152, 10.2215/CJN.0000000000000217.
Grubb, A., Non-invasive estimation of glomerular filtration rate (GFR). The Lund model: Simultaneous use of cystatin C- and creatinine-based GFR-prediction equations, clinical data and an internal quality check. Scand J Clin Lab Investig 70 (2010), 65–70, 10.3109/00365511003642535.
Inker, L.A., Eneanya, N.D., Coresh, J., et al. New creatinine- and cystatin C–based equations to estimate GFR without race. N Engl J Med 385 (2021), 1737–1749, 10.1056/NEJMoa2102953.
Pottel, H., Björk, J., Courbebaisse, M., et al. Development and validation of a modified full age spectrum creatinine-based equation to estimate glomerular filtration rate. A cross-sectional analysis of pooled data. Ann Intern Med 174 (2021), 183–191, 10.7326/M20-4366.
Nyman, U., Björk, J., Delanaye, P., et al. Rescaling creatinine makes GFR estimation equations generally applicable across populations - validation results for the Lund-Malmö equation in a French cohort of sub-Saharan ancestry. Clin Chem Lab Med 62 (2023), 421–427, 10.1515/cclm-2023-0496.
Delanaye, P., Cavalier, E., Stehlé, T., Pottel, H., Glomerular filtration rate estimation in adults: Myths and promises. Nephron 148 (2024), 408–414, 10.1159/000536243.
Pottel, H., Cavalier, E., Björk, J., et al. Standardization of serum creatinine is essential for accurate use of unbiased estimated GFR equations: Evidence from three cohorts matched on renal function. Clin Kidney J 15 (2022), 2258–2265, 10.1093/ckj/sfac182.
Delanaye, P., Rule, A.D., Schaeffner, E.S., et al. Performance of the European Kidney Function Consortium (EKFC) creatinine-based equation in United States cohorts. Kidney Int 105 (2024), 629–637, 10.1016/j.kint.2023.11.024.
Soveri, I., Berg, U.B., Björk, J., et al. Measuring GFR: A systematic review. Am J Kidney Dis 64 (2014), 411–424, 10.1053/j.ajkd.2014.04.010.
Delanaye, P., Ebert, N., Melsom, T., et al. Iohexol plasma clearance for measuring glomerular filtration rate in clinical practice and research: A review. Part 2: Why to measure glomerular filtration rate with iohexol?. Clin Kidney J 9 (2016), 682–699, 10.1093/ckj/sfw070.
Apperloo, A.J., de Zeeuw, D., Donker, A.J., de Jong, P.E., Precision of glomerular filtration rate determinations for long-term slope calculations is improved by simultaneous infusion of 125I-iothalamate and 131I-hippuran. J Am Soc Nephrol 7 (1996), 567–572, 10.1681/ASN.V74567.
Delgado, C., Baweja, M., Crews, D.C., et al. A unifying approach for GFR estimation: Recommendations of the NKF-ASN task force on reassessing the inclusion of race in diagnosing kidney disease. J Am Soc Nephrol 32 (2021), 2994–3015, 10.1681/ASN.2021070988.
Delanaye, P., Pottel, H., Botev, R., Inker, L.A., Levey, A.S., Con: Should we abandon the use of the MDRD equation in favour of the CKD-EPI equation?. Nephrol Dial Transpl 28 (2013), 1396–1403, 10.1093/ndt/gft006.
Delanaye, P., Cavalier, E., Depas, G., Chapelle, J.P., Krzesinski, J.M., New data on the intraindividual variation of cystatin C. Nephron Clin Pr 108 (2008), 246–249, 10.1159/000124327.
Schei, J., Stefansson, V.T.N., Mathisen, U.D., et al. Residual associations of inflammatory markers with eGFR after accounting for measured GFR in a community-based cohort without CKD. Clin J Am Soc Nephrol 11 (2016), 280–286, 10.2215/CJN.07360715.
Rule, A.D., Bailey, K.R., Lieske, J.C., Peyser, P.A., Turner, S.T., Estimating the glomerular filtration rate from serum creatinine is better than from cystatin C for evaluating risk factors associated with chronic kidney disease. Kidney Int 83 (2013), 1169–1176, 10.1038/ki.2013.7.
Melsom, T., Fuskevåg, O.M., Mathisen, U.D., et al. Estimated GFR is biased by non-traditional cardiovascular risk factors. Am J Nephrol 41 (2015), 7–15, 10.1159/000371557.
Shlipak, M.G., Matsushita, K., Arnlov, J., et al. Cystatin C versus creatinine in determining risk based on kidney function. N Engl J Med 369 (2013), 932–943, 10.1056/NEJMoa1214234.
Stehlé, T., Delanaye, P., Which is the best glomerular filtration marker : Creatinine, cystatin C or both?. Eur J Clin Investig, 54, 2024, e14278, 10.1111/eci.14278.
