• Lesley A Inker, Nwamaka D Eneanya, Josef Coresh, Hocine Tighiouart, Dan Wang, Yingying Sang, Deidra C Crews, Alessandro Doria, Michelle M Estrella, Marc Froissart, Morgan E Grams, Tom Greene, Anders Grubb, Vilmundur Gudnason, Orlando M Gutiérrez, Roberto Kalil, Amy B Karger, Michael Mauer, Gerjan Navis, Robert G Nelson, Emilio D Poggio, Roger Rodby, Peter Rossing, Andrew D Rule, Elizabeth Selvin, Jesse C Seegmiller, Michael G Shlipak, Vicente E Torres, Wei Yang, Shoshana H Ballew, Sara J Couture, Neil R Powe, Andrew S Levey, and Chronic Kidney Disease Epidemiology Collaboration.
• From the Division of Nephrology (L.A.I., S.J.C., A.S.L.) and the Institute for Clinical Research and Health Policy Studies (H.T.), Tufts Medical Center, Tufts Clinical and Translational Science Institute, Tufts University (H.T.), the Section on Genetics and Epidemiology, Joslin Diabetes Center (A.D.), and the Department of Medicine, Harvard Medical School (A.D.) - all in Boston; the Renal-Electrolyte and Hypertension Division, Perelman School of Medicine (N.D.E.), and the Departments of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics (W.Y.), University of Pennsylvania, Philadelphia; the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health and the Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Medical Institutions (J.C., D.W., Y.S., M.E.G., E.S., S.H.B.), the Division of Nephrology, Department of Medicine, Johns Hopkins University School of Medicine (D.C.C., M.E.G.), and the Department of Medicine, Division of Nephrology, University of Maryland School of Medicine (R.K.) - all in Baltimore; the Kidney Health Research Collaborative, San Francisco Veterans Affairs (VA) Medical Center and University of California, San Francisco (M.M.E., M.G.S.), the Division of Nephrology, Department of Medicine, San Francisco VA Health Care System and University of California, San Francisco (M.M.E.), and the Department of Medicine, Priscilla Chan and Mark Zuckerberg San Francisco General Hospital and University of California, San Francisco (N.R.P.) - all in San Francisco; the Clinical Trial Unit, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland (M.F.); the Division of Biostatistics, Department of Population Health Sciences, University of Utah Health, Salt Lake City (T.G.); the Department of Clinical Chemistry and Pharmacology, Institute of Laboratory Medicine, Lund University, Lund, Sweden (A.G.); the Faculty of Medicine, University of Iceland, Reykjavik, and the Icelandic Heart Association, Kopavogur - both in Iceland (V.G.); the Departments of Medicine and Epidemiology, University of Alabama at Birmingham, Birmingham (O.M.G.); the Departments of Laboratory Medicine and Pathology (A.B.K., J.C.S.), Pediatrics (M.M.), and Medicine (M.M.), University of Minnesota, Minneapolis, and the Division of Nephrology and Hypertension, Mayo Clinic, Rochester (A.D.R., V.E.T.) - all in Minnesota; the Faculty of Medical Sciences, University Medical Center Groningen, Groningen, the Netherlands (G.N.); the Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ (R.G.N.); the Department of Nephrology and Hypertension, Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland (E.D.P.); Rush University Medical Center, Chicago (R.R.); and Steno Diabetes Center Copenhagen and the Department of Clinical Medicine, University of Copenhagen - both in Copenhagen (P.R.).
• N. Engl. J. Med. 2021 Nov 4; 385 (19): 173717491737-1749.

BackgroundCurrent equations for estimated glomerular filtration rate (eGFR) that use serum creatinine or cystatin C incorporate age, sex, and race to estimate measured GFR. However, race in eGFR equations is a social and not a biologic construct.MethodsWe developed new eGFR equations without race using data from two development data sets: 10 studies (8254 participants, 31.5% Black) for serum creatinine and 13 studies (5352 participants, 39.7% Black) for both serum creatinine and cystatin C. In a validation data set of 12 studies (4050 participants, 14.3% Black), we compared the accuracy of new eGFR equations to measured GFR. We projected the prevalence of chronic kidney disease (CKD) and GFR stages in a sample of U.S. adults, using current and new equations.ResultsIn the validation data set, the current creatinine equation that uses age, sex, and race overestimated measured GFR in Blacks (median, 3.7 ml per minute per 1.73 m2 of body-surface area; 95% confidence interval [CI], 1.8 to 5.4) and to a lesser degree in non-Blacks (median, 0.5 ml per minute per 1.73 m2; 95% CI, 0.0 to 0.9). When the adjustment for Black race was omitted from the current eGFR equation, measured GFR in Blacks was underestimated (median, 7.1 ml per minute per 1.73 m2; 95% CI, 5.9 to 8.8). A new equation using age and sex and omitting race underestimated measured GFR in Blacks (median, 3.6 ml per minute per 1.73 m2; 95% CI, 1.8 to 5.5) and overestimated measured GFR in non-Blacks (median, 3.9 ml per minute per 1.73 m2; 95% CI, 3.4 to 4.4). For all equations, 85% or more of the eGFRs for Blacks and non-Blacks were within 30% of measured GFR. New creatinine-cystatin C equations without race were more accurate than new creatinine equations, with smaller differences between race groups. As compared with the current creatinine equation, the new creatinine equations, but not the new creatinine-cystatin C equations, increased population estimates of CKD prevalence among Blacks and yielded similar or lower prevalence among non-Blacks.ConclusionsNew eGFR equations that incorporate creatinine and cystatin C but omit race are more accurate and led to smaller differences between Black participants and non-Black participants than new equations without race with either creatinine or cystatin C alone. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases.).Copyright © 2021 Massachusetts Medical Society.

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