[en] [en] BACKGROUND: New equations to estimate glomerular filtration rate based on creatinine (eGFRcr), cystatin C (eGFRcys) or both (eGFRcr-cys) have been developed by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and the European Kidney Function Consortium (EKFC). There is a need to evaluate the performance of these equations in diverse European settings to inform implementation decisions, especially among people with key comorbid conditions.
METHODS: We performed a cross-sectional study including 6174 adults referred for single-point plasma clearance of iohexol in Stockholm, Sweden, with 9579 concurrent measurements of creatinine and cystatin C. We assessed the performance of the CKD-EPI 2009/2012/2021, EKFC 2021/2023, revised Lund-Malmö (RLM) 2011 and Caucasian, Asian, Pediatric and Adult (CAPA) 2014 equations against measured GFR (mGFR).
RESULTS: Mean age was 56 years, median mGFR was 62 mL/min/1.73 m2 and 40% were female. Comorbid conditions were common: cardiovascular disease (30%), liver disease (28%), diabetes (26%) and cancer (26%). All eGFRcr-cys equations had small bias and P30 (the percentage of estimated values within 30% of mGFR) close to 90%, and performed better than eGFRcr or eGFRcys equations. Among eGFRcr equations, CKD-EPI 2009 and CKD-EPI 2021 showed larger bias and lower P30 than EKFC 2021 and RLM. There were no meaningful differences in performance across eGFRcys equations. Findings were consistent across comorbid conditions, and eGFRcr-cys equations showed good performance in patients with liver disease, cancer and heart failure.
CONCLUSIONS: In conclusion, eGFRcr-cys equations performed best, with minimal variation among equations in this Swedish cohort. The lower performance of CKD-EPI eGFRcr equations compared with EKFC and RLM may reflect differences in population characteristics and mGFR methods. Implementing eGFRcr equations will require a trade-off between accuracy and uniformity across regions.
Disciplines :
Urology & nephrology
Author, co-author :
Fu, Edouard L ; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA ; Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden ; Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
Levey, Andrew S; Division of Nephrology, Department of Internal Medicine, Tufts Medical Center, Boston, MA, USA
Coresh, Josef; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
Grams, Morgan E; Division of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA
Faucon, Anne-Laure ; Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden ; INSERM UMR 1018, Department of Clinical Epidemiology, Paris-Saclay University, Paris, France
Elinder, Carl-Gustaf; Division of Renal Medicine, Department of Clinical Intervention, and Technology, Karolinska University Hospital and Karolinska Institute, Stockholm, Sweden
Dekker, Friedo W; Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
Delanaye, Pierre ; Université de Liège - ULiège > Département de pharmacie > Chimie médicale ; Department of Nephrology-Dialysis-Apheresis, Hôpital Universitaire Carémeau, Nîmes, France
Inker, Lesley A; Division of Nephrology, Department of Internal Medicine, Tufts Medical Center, Boston, MA, USA
Carrero, Juan-Jesus ; Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden ; Division of Nephrology, Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden
Language :
English
Title :
Accuracy of GFR estimating equations based on creatinine, cystatin C or both in routine care.
Swedish Research Council [SE] DKF - Dutch Kidney Foundation [NL] NWO - Netherlands Organisation for Scientific Research [NL] KI - Karolinska Institute [SE]
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