Pierre Delanaye1,2, Jonas Björk3,4, Marie Courbebaisse5, Lionel Couzi6, Natalie Ebert7, Björn O Eriksen8, R Neil Dalton9, Laurence Dubourg10, Francois Gaillard11, Cyril Garrouste12, Anders Grubb13, Lola Jacquemont14, Magnus Hansson15, Nassim Kamar16, Edmund J Lamb17, Christophe Legendre18, Karin Littmann19, Christophe Mariat20, Toralf Melsom8, Lionel Rostaing21, Andrew D Rule22, Elke Schaeffner7, Per-Ola Sundin23, Ulla B Berg24, Kajsa Åsling-Monemi24, Luciano Selistre25, Anna Åkesson3,4, Anders Larsson26, Arend Bökenkamp27, Hans Pottel28, Ulf Nyman29. 1. Department of Nephrology-Dialysis-Transplantation, University of Liège, CHU Sart Tilman, Liège, Belgium. 2. Department of Nephrology-Dialysis-Apheresis, Hopital Universitaire Carémeau, Nîmes, France. 3. Division of Occupational and Environmental Medicine, Lund University, Lund, Sweden. 4. Clinical Studies Sweden, Forum South, Skåne University Hospital, Lund, Sweden. 5. Physiology Department, Georges Pompidou European Hospital, Assistance Publique Hôpitaux de Paris, Paris University, Paris, France. 6. CHU de Bordeaux, Néphrologie-Transplantation-Dialyse, Université de Bordeaux, France. 7. Charité Universitätsmedizin Berlin, Institute of Public Health, Berlin, Germany. 8. Metabolic and Renal Research Group, UiT The Arctic University of Norway, Tromsö, Norway. 9. The Wellchild Laboratory, Evelina London Children's Hospital, London, UK. 10. 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. 11. Service de transplantation et immunologie clinique, Hopital Edouard Herriot, Hospices civils de Lyon, Lyon, France. 12. Department of Nephrology, Clermont-Ferrand University Hospital, Clermont-Ferrand, France. 13. Department of Clinical Chemistry, Skåne University Hospital, Lund, Lund University, Sweden. 14. Renal Transplantation Department, CHU Nantes, Nantes University, Nantes, France. 15. Function Area Clinical Chemistry, Karolinska University Laboratory, Karolinska University Hospital Huddinge and Department of Laboratory Medicine, Karolinska Institute, Stockholm, Sweden. 16. Department of Nephrology, Dialysis and Organ Transplantation, CHU Rangueil, INSERM U1043, IFR-BMT, University Paul Sabatier, Toulouse, France. 17. Clinical Biochemistry, East Kent Hospitals University NHS Foundation Trust, Canterbury, UK. 18. Hôpital Necker, Assistance Publique-Hôpitaux de Paris and Université Paris, Paris, France. 19. Department of Medicine Huddinge, Karolinska Institute, Huddinge, Sweden. 20. Service de Néphrologie, Dialyse et Transplantation Rénale, Hôpital Nord, CHU de Saint-Etienne, France. 21. Service de Néphrologie, Hémodialyse, Aphérèses et Transplantation Rénale, Hôpital Michallon, CHU Grenoble-Alpes, France. 22. Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA. 23. Department of Geriatrics, School of Medical Sciences, Örebro University, Örebro, Sweden. 24. Department of Clinical Science, Intervention and Technology, Division of Pediatrics, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden. 25. Mestrado em Ciências da Saúde - Universidade Caxias do Sul Foundation CAPES, Brazil. 26. Department of Pediatric Nephrology, Emma Children's Hospital, Amsterdam University Medical Centers, Amsterdam, The Netherlands. 27. Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden. 28. Department of Public Health and Primary Care, KU Leuven Campus Kulak Kortrijk, Kortrijk, Belgium. 29. Department of Translational Medicine, Division of Medical Radiology, Lund University, Malmö, Sweden.
Abstract
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.
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.