chronic kidney disease; drug adjustment; glomerular filtration rate; Creatinine; Body Mass Index; Cross-Sectional Studies; Glomerular Filtration Rate; Humans; Renal Insufficiency, Chronic; Pharmacology; Pharmacology (medical)
Abstract :
[en] AIM: The Cockcroft-Gault (CG) creatinine-based equation is still used to estimate glomerular filtration rate (eGFR) for drug dosage adjustment. Incorrect eGFR may lead to hazardous over- or underdosing.
METHODS: In a cross-sectional analysis, CG was validated against measured GFR (mGFR) in 14 804 participants and compared with the Modification-of-Diet-in-Renal-Diseases (MDRD), Chronic-Kidney-Disease-Epidemiology (CKD-EPI), Lund-Malmö-Revised (LMR) and European-Kidney-Function-Consortium (EKFC) equations. Validation focused on bias, imprecision and accuracy (percentage of estimates within ±30% of mGFR, P30), overall and stratified for mGFR, age and body mass index at mGFR <60 mL/min, as well as classification in mGFR stages.
RESULTS: The CG equation performed worse than the other equations, overall and in mGFR, age and BMI subgroups in terms of bias (systematic overestimation), imprecision and accuracy except for patients ≥65 years where bias and P30 were similar to MDRD and CKD-EPI, but worse than LMR and EKFC. In subjects with mGFR <60 mL/min and at BMI 18.5-25 kg/m2 , all equations performed similarly, and for BMI < 18.5 kg/m2 CG and LMR had the best results though all equations had poor P30-accuracy. At BMI ≥ 25 kg/m2 the bias of the CG increased with increasing BMI (+17.2 mL/min at BMI ≥ 40 kg/m2 ). The four more recent equations also classified mGFR stages better than CG.
CONCLUSIONS: The CG equation showed poor ability to estimate GFR overall and in analyses stratified for mGFR, age and BMI. CG was inferior to correctly classify the patients in the mGFR staging compared to more recent creatinine-based equations.
Disciplines :
Urology & nephrology
Author, co-author :
DELANAYE, Pierre ; Centre Hospitalier Universitaire de Liège - CHU > > Service de néphrologie ; Department of Nephrology-Dialysis-Apheresis, Hopital 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
Courbebaisse, Marie; Physiology Department, Georges Pompidou European Hospital, Assistance Publique Hôpitaux de Paris, Paris University, Paris, France
Couzi, Lionel; CHU de Bordeaux, Néphrologie-Transplantation-Dialyse, Université de Bordeaux, France
Ebert, Natalie; Charité Universitätsmedizin Berlin, Institute of Public Health, Berlin, Germany
Eriksen, Björn O; Metabolic and Renal Research Group, UiT The Arctic University of Norway, Tromsö, Norway
Dalton, R Neil; The Wellchild Laboratory, Evelina London Children's Hospital, London, UK
Dubourg, Laurence; Service de Néphrologie, Dialyse, Hypertension et Exploration Fonctionnelle Rénale, Hospices Civils de Lyon, Hôpital E. Herriot, University of Lyon 1, CNRS UMR 5305, Lyon, France
Gaillard, Francois; Service de transplantation et immunologie clinique, Hopital Edouard Herriot, Hospices civils de Lyon, Lyon, France
Garrouste, Cyril; Department of Nephrology, Clermont-Ferrand University Hospital, Clermont-Ferrand, France
Grubb, Anders; Department of Clinical Chemistry, Skåne University Hospital, Lund, Lund University, Sweden
Hansson, Magnus; Function Area Clinical Chemistry, Karolinska University Laboratory, Karolinska University Hospital Huddinge and Department of Laboratory Medicine, Karolinska Institute, Stockholm, Sweden
Kamar, Nassim; Department of Nephrology, Dialysis and Organ Transplantation, CHU Rangueil, INSERM U1043, IFR-BMT, University Paul Sabatier, Toulouse, France
Lamb, Edmund J; Clinical Biochemistry, East Kent Hospitals University NHS Foundation Trust, Canterbury, UK
Legendre, Christophe; Hôpital Necker, Assistance Publique-Hôpitaux de Paris and Université Paris, Paris, France
Littmann, Karin; Department of Medicine Huddinge, Karolinska Institute, Huddinge, Sweden
Mariat, Christophe; Service de Néphrologie, Dialyse et Transplantation Rénale, Hôpital Nord, CHU de Saint-Etienne, France
Melsom, Toralf; Metabolic and Renal Research Group, UiT The Arctic University of Norway, Tromsö, Norway
Rostaing, Lionel; Service de Néphrologie, Hémodialyse, Aphérèses et Transplantation Rénale, Hôpital Michallon, CHU Grenoble-Alpes, France
Rule, Andrew D; Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
Schaeffner, Elke; Charité Universitätsmedizin Berlin, Institute of Public Health, Berlin, Germany
Sundin, Per-Ola; Department of Geriatrics, School of Medical Sciences, Örebro University, Örebro, Sweden
Berg, Ulla B; Department of Clinical Science, Intervention and Technology, Division of Pediatrics, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
Åsling-Monemi, Kajsa; Department of Clinical Science, Intervention and Technology, Division of Pediatrics, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
Selistre, Luciano; Mestrado em Ciências da Saúde - Universidade Caxias do Sul Foundation CAPES, Brazil
Åkesson, Anna; Division of Occupational and Environmental Medicine, Lund University, Lund, Sweden ; Clinical Studies Sweden, Forum South, Skåne University Hospital, Lund, Sweden
Larsson, Anders; Department of Pediatric Nephrology, Emma Children's Hospital, Amsterdam University Medical Centers, Amsterdam, The Netherlands
Bökenkamp, Arend; Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden
Pottel, Hans ; Université de Liège - ULiège > Département des sciences cliniques ; Department of Public Health and Primary Care, KU Leuven Campus Kulak Kortrijk, Kortrijk, Belgium
Nyman, Ulf; Department of Translational Medicine, Division of Medical Radiology, Lund University, Malmö, Sweden
We sincerely thank Eric P. Cohen, New York for his help in editing the manuscript. Primary funding source: Swedish Research Council (Vetenskapsrådet; grant no. 2019‐00198).The results presented in this paper have not been published previously in whole or part. U. Nyman has received lecture fees from GE Healthcare AB. M. Courbebaisse has received grant support from BIOPAL, USA. N. Dalton is a Director of and minority shareholder in a University/NHS spin‐out company, SpOtOn Clinical Diagnostics, and has grant support from NHS Health Technology Assessment and the Juvenile Diabetes Research Foundation. N. Ebert has received lecture fees from Siemens Healthineer and Roche Diagnostics. B.O. Eriksen has received lecture fees from Sanofi‐Aventis. N. Kamar has received consulting fees or paid advisory boards, lecture fees and travel support from the following companies: Abbvie, Amgen, Astellas, Chiesi, Fresenius Medical Care, Gilead, Merck Sharp and Dohme, Neovii, Novartis, Roche, Sanofi and Shire. C. Legendre received consulting fees or paid advisory boards from CSL Behring and Novartis, and lecture fees from Sandoz. E. Schaeffner has received lecture fees from Siemens Healthineers and Fresenius Kabi. All remaining authors declared no competing interests.Professor J. Björk has funding from the Swedish Research Council (VR) to conduct large‐scale epidemiological studies linked with registered data from healthcare (Vetenskapsrådet; grant no. 2019‐00198). This funding source was at no time involved in the design, analysis, presentation or interpretation of the results from the present study.
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. 2021;174(2):183-191.
Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604-612.
Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron. 1976;16(1):31-41.
Verbeeck RK, Musuamba FT. Pharmacokinetics and dosage adjustment in patients with renal dysfunction. Eur J Clin Pharmacol. 2009;65(8):757-773.
Dreisbach AW, Flessner MF. Drug metabolism and chronic kidney disease. In: Kimmel PL, Rosenberg MK, eds. Chronic Renal Disease. Vol First Edit. Elsevier; 2014:674-681.
Grubb A, Nyman U, Björk J, et al. Simple cystatin C-based prediction equations for glomerular filtration rate compared with the modification of diet in renal disease prediction equation for adults and the Schwartz and the Counahan-Barratt prediction equations for children. Clin Chem. 2005;51(0009-9147):1420-1431.
Inker LA, Schmid CH, Tighiouart H, et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med. 2012;367(1):20-29.
Nyman U, Grubb A, Larsson A, et al. The revised Lund-Malmö GFR estimating equation outperforms MDRD and CKD-EPI across GFR, age and BMI intervals in a large Swedish population. Clin Chem Lab Med. 2014;52(6):815-824.
EMA. http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2014/02/WC500162133.pdf
FDA. Guidance for Industry Pharmacokinetics in Patients with Impaired Renal Function — Study Design, Data Analysis, and Impact on Dosing and Labeling. FDA. 2010;(March).
Matzke GR, Aronoff GR, Atkinson AJ Jr, et al. Drug dosing consideration in patients with acute and chronic kidney disease-a clinical update from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int. 2011;80(11):1122-1137.
Delanaye P, Krzesinski J-M. Indexing of renal function parameters by body surface area: intelligence or folly? Nephron Clin Pract. 2011;119(4):c289-c292.
KDIGO clinical practice guideline for the diagnosis, evaluation, prevention, and treatment of chronic kidney disease-mineral and bone disorder (CKD-MBD). Kidney Int Suppl. 2009;(0098-6577 [Print]):S1-130.
Froissart M, Rossert J, Jacquot C, Paillard M, Houillier P. Predictive performance of the modification of diet in renal disease and Cockcroft-Gault equations for estimating renal function. J Am Soc Nephrol. 2005;16(3):763-773.
Stevens LA, Nolin TD, Richardson MM, et al. Comparison of drug dosing recommendations based on measured GFR and kidney function estimating equations. Am J Kidney Dis. 2009;54(1):33-42.
Michels WM, Grootendorst DC, Verduijn M, Elliott EG, Dekker FW, Krediet RT. Performance of the Cockcroft-Gault, MDRD, and new CKD-EPI formulas in relation to GFR, age, and body size. Clin J Am Soc Nephrol. 2010;5(6):1003-1009.
Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med. 1999;130(6):461-470.
Björk J, Nyman U, Delanaye P, et al. A novel method for creatinine adjustment makes the revised Lund-Malmö GFR estimating equation applicable in children. Scand J Clin Lab Invest. 2020;80(6):456-463.
Pottel H, Delanaye P, Schaeffner ES, et al. Estimating glomerular filtration rate for the full age spectrum from serum creatinine and cystatin C. Nephrol Dial Transplant. 2017;32:497-507.
Piéroni L, Delanaye P, Boutten A, et al. A multicentric evaluation of IDMS-traceable creatinine enzymatic assays. Clin Chim Acta. 2011;412(23-24):2070-2075. https://doi.org/10.1016/j.cca.2011.07.012
Soveri I, Berg UB, Björk J, et al. Measuring GFR: a systematic review. Am J Kidney Dis. 2014;64(3):411-424.
Delanaye P, Ebert N, Melsom T, et al. Iohexol plasma clearance for measuring glomerular filtration rate in clinical practice and research: a review. Part 1: How to measure glomerular filtration rate with iohexol? Clin Kidney J. 2016;9(5):682-699.
Du Bois D, Du Bois EF. A formula to estimate the approximate surface area if height and weight be known. Arch Intern Med. 1916;17:862-871.
KDIGO 2012 Clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl. 2013;3(1):1-150.
National Kidney Foundation. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification and stratification. Am J Kidney Dis. 2002;39(suppl. 1):1-266. https://doi.org/10.1634/theoncologist.2011-S2-45
Earley A, Miskulin D, Lamb EJ, Levey AS, Uhlig K. Estimating equations for glomerular filtration rate in the era of creatinine standardization: a systematic review. Ann Intern Med. 2012;156(11):785-795.
Luis-Lima S, Escamilla-Cabrera B, Negrín-Mena N, et al. CKD staging with cystatin C or creatinine-based formulas: flipping the coin. Nephrol Dial Transplant. 2019;34(2):287-294.
Delanaye P, Jager KJ, Bökenkamp A, et al. CKD: a call for an age-adapted definition. J Am Soc Nephrol. 2019;30(10):1785-1805.
Björk J, Grubb A, Sterner G, Nyman U. Revised equations for estimating glomerular filtration rate based on the Lund-Malmö Study cohort. Scand J Clin Lab Invest. 2011;71(3):232-239.
Bouquegneau A, Vidal-Petiot E, Moranne O, et al. Creatinine-based equations for the adjustment of drug dosage in an obese population. Br J Clin Pharmacol. 2016;81(2):349-361.
Lemoine S, Guebre-Egziabher F, Sens F, et al. Accuracy of GFR estimation in obese patients. Clin J Am Soc Nephrol. 2014;9(4):720-727.
Schaeffner ES, Ebert N, Delanaye P, et al. Two novel equations to estimate kidney function in persons aged 70 years or older. Ann Intern Med. 2012;157(7):471-481.
Flamant M, Haymann JP, Vidal-Petiot E, et al. GFR estimation using the Cockcroft-Gault, MDRD study, and CKD-EPI equations in the elderly. Am J Kidney Dis. 2012;60(5):847-849.
Björk J, Grubb A, Gudnason V, et al. Comparison of glomerular filtration rate estimating equations derived from creatinine and cystatin C: validation in the age, gene/environment susceptibility-Reykjavik elderly cohort. Nephrol Dial Transplant. 2018;33(8):1380-1388.
Delanaye P, Cavalier E, Radermecker RPP, et al. Estimation of GFR by different creatinine- and cystatin-C-based equations in anorexia nervosa. Clin Nephrol. 2009;71(5):482-491.
Agarwal R, Delanaye P. Glomerular filtration rate: when to measure and in which patients? Nephrol Dial Transplant. 2019;34(12):2001-2007.
Delanaye P, Melsom T, Ebert N, 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. 2016;9(5):700-704.
Nyman U, Grubb A, Lindström V, Björk J. Accuracy of GFR estimating equations in a large Swedish cohort: implications for radiologists in daily routine and research. Acta Radiol. 2017;58(3):367-375.
Delanaye P. Kidney Function. 2019. https://doi.org/10.1016/B978-0-323-54945-5.00010-2
Delanaye P, Cavalier E, Pottel H. Serum creatinine: not so simple! Nephron. 2017;136(4):302-308.
Salvi F, Marchetti A, D'Angelo F, Boemi M, Lattanzio F, Cherubini A. Adverse drug events as a cause of hospitalization in older adults. Drug Saf. 2012;35(Supplem 1):29-45.
Delanaye P, Guerber F, Scheen A, et al. Discrepancies between the Cockcroft-Gault and Chronic Kidney Disease Epidemiology (CKD-EPI) equations: Implications for refining drug dosage adjustment strategies. Clin Pharmacokinet. 2017;56(2):193-205.
Delanaye P, Mariat C, Maillard N, Krzesinski JM, Cavalier E. Are the creatinine-based equations accurate to estimate glomerular filtration rate in african american populations? Clin J Am Soc Nephrol. 2011;6(4):906-912. https://doi.org/10.2215/CJN.10931210
American Society of Nephrology (ASN), National Kidney Foundation (NKF). Establishing a task force to reassess the inclusion of race in diagnosing kidney disease. https://www.kidneynews.org/view/news/policy-advocacy/leading-edge/asn-and-nkf-establishing-task-force-to-reassess-the-inclusion-of-race-in-diagnosing-kidney-diseases.xml
K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis. 2002;39(2 Suppl 1):S1-S266.
