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New creatinine- and cystatin C-based equations to estimate GFR without race
Open accessAbstract
BACKGROUND: Current 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. METHODS: We 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. RESULTS: ; 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. CONCLUSIONS: New 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.).
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“Hence, the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equation was refit without the race variable and should be used for everyone (17,18).”
From 11. Chronic Kidney Disease and Risk Management: Standards of Care in Diabetes—2025 (2025) · cites this paper as [17]
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“Adding cystatin C to serum creatinine improves the accuracy of race-neutral eGFR equations (476,477)”
From Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus (2023) · cites this paper as [476]
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“The combination of both filtration markers (creatinine and cystatin C) is more accurate and would support better clinical decisions than either marker alone (16,19).”
From 11. Chronic Kidney Disease and Risk Management: Standards of Care in Diabetes—2026 (2026) · cites this paper as [16]
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“Sensitivity analyses were also performed using eGFR calculated determined using the 2021 creatinine-based CKD-EPI formula43, and separately using the combined creatinine-cystatin C CKD-EPI formula (Supplementary Appendix 2)19.”
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“Risk of CVD increases progressively with lower levels of eGFR and, in those with advanced CKD, structural abnormalities of the heart, HF, and sudden death are particular features.679,680,[686][687][688]”
From 2023 ESC guidelines for the management of cardiovascular disease in patients with diabetes. (2023) · cites this paper as [680]
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“This level of eGFR is associated with increased risk of CKD progression and CVD.43,679,680”
From 2023 ESC guidelines for the management of cardiovascular disease in patients with diabetes. (2023) · cites this paper as [680]
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“Risk of CVD increases progressively with lower levels of eGFR and, in those with advanced CKD, structural abnormalities of the heart, HF, and sudden death are particular features.679,680,[686][687][688]”
From 2023 ESC guidelines for the management of cardiovascular disease in patients with diabetes. (2023) · cites this paper as [680]
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“Since the recruitment of FLOW trial participants, a new CKD-EPI formula without race as a factor has been recommended; a pre-specified supplementary analysis has now been added to evaluate the impact of the updated formula on the results [16].”
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Research works printed but not linked: 2
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Nemet, I., Li, X. S., Haghikia, A., Li, L., Wilcox, J. D., Romano, K. A., Buffa, J. A., Witkowski, M., Demuth, I., König, M., et al. (2023) · European Heart Journal · doi:10.1093/eurheartj/ehad333 · Cited by 131
Multi-ancestry polygenic mechanisms of type 2 diabetes
Smith, K., Deutsch, A. J., McGrail, C., Kim, H., Hsu, S. C., Huerta‐Chagoya, A., Mandla, R., Schroeder, P. H., Westerman, K. E., Szczerbiński, Ł., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-02865-3 · Cited by 140
The nephropathy of sickle cell trait and sickle cell disease
Ataga, K. I., Saraf, S. L., & Derebail, V. K. (2022) · Nature Reviews Nephrology · doi:10.1038/s41581-022-00540-9 · Cited by 125
Ferrell, M., Wang, Z., Anderson, J. T., Li, X. S., Witkowski, M., DiDonato, J. A., Hilser, J. R., Hartiala, J., Haghikia, A., Čajka, T., et al. (2024) · Nature Medicine · doi:10.1038/s41591-023-02793-8 · Cited by 129
Segar, M. W., Hall, J. L., Jhund, P., Powell-Wiley, T., Morris, A., Kao, D. P., Fonarow, G., Hernandez, R., Ibrahim, N. E., Rutan, C., et al. (2022) · JAMA cardiology · doi:10.1001/jamacardio.2022.1900 · Cited by 109
A toolbox for surfacing health equity harms and biases in large language models
Pfohl, S. R., Cole-Lewis, H., Sayres, R., Neal, D., Asiedu, M., Dieng, A., Tomasev, N., Rashid, Q. M., Azizi, S., Rostamzadeh, N., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-03258-2 · Cited by 113
Carrero, J. J., Fu, E. L., Sang, Y., Ballew, S. H., Evans, M., Elinder, C., Barany, P. F., Inker, L. A., Levey, A. S., Coresh, J., et al. (2023) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2023.04.002 · Cited by 117
Self-citationVlasschaert, C., McNaughton, A. J. M., Chong, M., Cook, E. K., Hopman, W. M., Kestenbaum, B. R., Robinson‐Cohen, C., Garland, J. S., Moran, S. M., Paré, G., et al. (2022) · Journal of the American Society of Nephrology · doi:10.1681/asn.2021060774 · Cited by 113
Stocker, H. R., Beyer, L., Trares, K., Perna, L., Rujescu, D., Holleczek, B., Beyreuther, K. T., Gerwert, K. B., Schöttker, B., & Brenner, H. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.52387 · Cited by 116
11. Chronic Kidney Disease and Risk Management: Standards of Care in Diabetes—2026
American Diabetes Association Professional Practice Committee for Diabetes*, Bajaj, M., McCoy, R. G., Balapattabi, K., Bannuru, R. R., Bellini, N. J., Bennett, A. K., Beverly, E. A., Briggs Early, K., ChallaSivaKanaka, S., et al. (2026) · Diabetes Care · doi:10.2337/dc26-s011 · Cited by 108
What should European nephrology do with the new CKD-EPI equation?
Gansevoort, R. T., Anders, H., Cozzolino, M. G., Fliser, D., Fouque, D. P., Ortíz, A., Soler, M. J., & Wanner, C. (2022) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfac254 · Cited by 106
Artificial intelligence-enabled decision support in nephrology
Loftus, T. J., Shickel, B., Ozrazgat‐Baslanti, T., Ren, Y., Glicksberg, B. S., Cao, J., Singh, K., Chan, L., Nadkarni, G. N., & Bihorac, A. (2022) · Nature Reviews Nephrology · doi:10.1038/s41581-022-00562-3 · Cited by 115
D’Andrea, E., Wexler, D. J., Kim, S. C., Paik, J. M., Alt, E. M., & Patorno, E. (2023) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2022.6664 · Cited by 105
Contributors to Serum NfL Levels in People without Neurologic Disease
Fitzgerald, K. C., Sotirchos, E. S., Smith, M. D., Lord, H., DuVal, A., Mowry, E. M., & Calabresi, P. A. (2022) · Annals of Neurology · doi:10.1002/ana.26446 · Cited by 101
Ratziu, V., Harrison, S. A., Loustaud-Ratti, V., Bureau, C., Lawitz, E., Abdelmalek, M., Alkhouri, N., Francque, S., Girma, H., Darteil, R., et al. (2023) · Journal of Hepatology · doi:10.1016/j.jhep.2022.10.023 · Cited by 101
Herrington, W. G., Judge, P. K., Grams, M. E., & Wanner, C. (2025) · The Lancet · doi:10.1016/s0140-6736(25)01942-7 · Cited by 124
Self-citationClinical Impact of the Refit CKD-EPI 2021 Creatinine-Based eGFR Equation
Meeusen, J. W., Kasozi, R. N., Larson, T. S., & Lieske, J. C. (2022) · Clinical Chemistry · doi:10.1093/clinchem/hvab282 · Cited by 101
Haines, R. W., Fowler, A. J., Liang, K., Pearse, R. M., Larsson, A. O., Puthucheary, Z., & Prowle, J. R. (2023) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.0000000000000203 · Cited by 102
Navaneethan, S. D., Bansal, N., Cavanaugh, K. L., Chang, A. R., Crowley, S. T., Delgado, C., Estrella, M. M., Ghossein, C., Ikizler, T. A., Koncicki, H. M., et al. (2024) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2024.08.003 · Cited by 116
Self-citationHeerspink, H. J. L., Apperloo, E., Davies, M., Dicker, D., Kandler, K., Rosenstock, J., Sørrig, R., Lawson, J., Zeuthen, N., & Cherney, D. (2023) · Diabetes Care · doi:10.2337/dc22-1889 · Cited by 98
Chen, D. C., Shlipak, M. G., Scherzer, R., Bauer, S. R., Potok, O., Rifkin, D. E., Ix, J. H., Muiru, A. N., Hsu, C., & Estrella, M. M. (2022) · JAMA Network Open · doi:10.1001/jamanetworkopen.2021.48940 · Cited by 100
Self-citationGlobal, Race-Neutral Reference Equations and Pulmonary Function Test Interpretation
Moffett, A. T., Bowerman, C., Stanojevic, S., Eneanya, N. D., Halpern, S. D., & Weissman, G. E. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.16174 · Cited by 102
Self-citationMuscle mass and estimates of renal function: a longitudinal cohort study
Groothof, D., Post, A., Polinder‐Bos, H. A., Erler, N. S., Flores-Guerrero, J. L., Kootstra‐Ros, J. E., Pol, R. A., de Borst, M. H., Gansevoort, R. T., Gans, R. O. B., et al. (2022) · Journal of Cachexia Sarcopenia and Muscle · doi:10.1002/jcsm.12969 · Cited by 108
Cumulative Incidence of Mortality Associated with Cardiovascular–Kidney–Metabolic (CKM) Syndrome
Claudel, S. E., Schmidt, I. M., Waikar, S. S., & Verma, A. (2025) · Journal of the American Society of Nephrology · doi:10.1681/asn.0000000637 · Cited by 99
Delanaye, P., Vidal‐Petiot, E., Björk, J., Ebert, N., Eriksen, B. O., Dubourg, L. D., GRUBB, A. O., Hansson, M. E. A., Littmann, K., Mariat, C., et al. (2022) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfac241 · Cited by 92
Self-citationNew strategies to improve clinical outcomes for diabetic kidney disease
Forst, T. M., Mathieu, C., Giorgino, F., Wheeler, D. C., Παπάνας, Ν., Schmieder, R. E., Halabi, A., Schnell, O., Streckbein, M., & Tuttle, K. R. (2022) · BMC Medicine · doi:10.1186/s12916-022-02539-2 · Cited by 96
George, C., Echouffo-Tcheugui, J. B., Jaar, B. G., Okpechi, I. G., & Kengne, A. P. (2022) · BMC Medicine · doi:10.1186/s12916-022-02438-6 · Cited by 91
Heerspink, H. J. L., Agarwal, R., Bakris, G. L., Cherney, D. Z. I., Lam, C. S. P., Neuen, B. L., Sarafidis, P. A., Tuttle, K. R., Wanner, C., BRINKER, M. D., et al. (2024) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfae132 · Cited by 102
Self-citationHigh-sensitivity troponins and mortality in the general population
McEvoy, J. W., Daya, N. R., Tang, O., Fang, M., Ndumele, C. E., Coresh, J., Christenson, R. H., & Selvin, E. (2023) · European Heart Journal · doi:10.1093/eurheartj/ehad328 · Cited by 88
Self-citationSchlosser, P., Scherer, N., Grundner-Culemann, F., Monteiro-Martins, S., Haug, S., Steinbrenner, I., Uluvar, B., Wuttke, M., Cheng, Y., Ekici, A. B., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01409-8 · Cited by 92
Self-citationMoving from Evidence to Implementation of Breakthrough Therapies for Diabetic Kidney Disease
Tuttle, K. R., Wong, L., St. Peter, W., Roberts, G., Rangaswami, J., Mottl, A., Kliger, A. S., Harris, R. C., Gee, P. O., Fowler, K., et al. (2022) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.02980322 · Cited by 87
Glomerular filtration in the aging population
Noronha, I. L., Santa-Catharina, G. P., Andrade, L., Coelho, V. A., Filho, W. J., & Elias, R. M. (2022) · Frontiers in Medicine · doi:10.3389/fmed.2022.769329 · Cited by 110
Handelsman, Y., Anderson, J. E., Bakris, G. L., Ballantyne, C. M., Bhatt, D. L., Bloomgarden, Z. T., Bozkurt, B., Budoff, M. J., Butler, J., Cherney, D. Z. I., et al. (2024) · Metabolism · doi:10.1016/j.metabol.2024.155931 · Cited by 99
Self-citationVariation in secondary prevention of coronary heart disease: the INTERASPIRE study
McEvoy, J. W., Jennings, C. S., Kotseva, K., Bacquer, D. D., Backer, G. D., Erlund, I., Vihervaara, T., Lip, G. Y. H., Ray, K. K., Rydén, L., et al. (2024) · European Heart Journal · doi:10.1093/eurheartj/ehae558 · Cited by 95
Measurement of kidney function in Malawi, South Africa, and Uganda: a multicentre cohort study
Fabian, J., Kalyesubula, R., Mkandawire, J., Hansen, C. H., Nitsch, D., Musenge, E., Nakanga, W. P., Prynn, J. E., Dreyer, G., Snyman, T., et al. (2022) · The Lancet Global Health · doi:10.1016/s2214-109x(22)00239-x · Cited by 87
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The Growing Challenge of Chronic Kidney Disease: An Overview of Current Knowledge
Borg, R., Carlson, N., Søndergaard, J., & Persson, F. (2023) · International Journal of Nephrology · doi:10.1155/2023/9609266 · Cited by 115
Screening, identifying, and treating chronic kidney disease: why, who, when, how, and what?
Farrell, D. R., & Vassalotti, J. A. (2024) · BMC Nephrology · doi:10.1186/s12882-024-03466-5 · Cited by 95
The Impact of Health Care Algorithms on Racial and Ethnic Disparities
Siddique, S. M., Tipton, K. N., Leas, B. F., Jepson, C., Aysola, J., Cohen, J. B., Flores, E. J., Harhay, M. O., Schmidt, H., Weissman, G. E., et al. (2024) · Annals of Internal Medicine · doi:10.7326/m23-2960 · Cited by 88
Matsushita, K., Kaptoge, S. K., Hageman, S. H. J., Sang, Y., Ballew, S. H., Grams, M. E., Surapaneni, A., Sun, L., Ärnlöv, J., Božić, M., et al. (2022) · European Journal of Preventive Cardiology · doi:10.1093/eurjpc/zwac176 · Cited by 84
Self-citationFu, E. L., Levey, A. S., Coresh, J., Elinder, C., Rotmans, J. I., Dekker, F. W., Paik, J. M., Barany, P. F., Grams, M. E., Inker, L. A., et al. (2023) · Journal of the American Society of Nephrology · doi:10.1681/asn.0000000000000128 · Cited by 86
Self-citationHe, J., Bundy, J. D., Geng, S., Tian, L., He, H., Li, X., Ferdinand, K. C., Anderson, A. H., DORANS, K. S., Vasan, R. S., et al. (2023) · Annals of Internal Medicine · doi:10.7326/m23-0507 · Cited by 87
Metadata
- Authors
- Inker, L. A., Eneanya, N. D., Coresh, J., Tighiouart, H., Wang, D., Sang, Y., Crews, D. C., Doria, A., Estrella, M. M., Froissart, M., Grams, M. E., Greene, T., Grubb, A., Gudnason, V., Gutiérrez, O. M., Kalil, R., Karger, A. B., Mauer, M., Navis, G., Nelson, R. G., Poggio, E. D., Rodby, R., Rossing, P., Rule, A. D., Selvin, E., Seegmiller, J. C., Shlipak, M. G., Torres, V. E., Yang, W., Ballew, S. H., Couture, S. J., Powe, N. R., & Levey, A. S.
- Affiliations
- Tufts University (US)
- ORCID
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 2021-11-04
- Volume
- 385
- Issue
- 19
- Pages
- 1737-1749
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- PMC
- PMC8822996
- OpenAlex
- W3201595862
- Semantic Scholar
- 13337143c398a584e3076a1b3be0178611b6e455
- Cited by
- 4,695
- References
- 34
- Citations by year
- 2026: 1301 · 2025: 1222 · 2024: 1008 · 2023: 729 · 2022: 394 · 2021: 33
- FWCI
- 373.01
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- New England Journal of Medicine (publishedVersion)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, other-oa)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion, other-oa)
- SERVAL (Université de Lausanne) (publishedVersion, other-oa)
- PubMed Central (acceptedVersion)
- IRIS (submittedVersion)
- Opin vísindi (Opin vísindi) (submittedVersion, cc-by-nc-sa)
- eScholarship (California Digital Library) (submittedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- Opin vísindi (Opin vísindi) (submittedVersion, other-oa)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- Funders
- Clinical Translational Science Center
- Gilead Sciences
- Medical Faculty of the University of Lund (Grant 05196)
- National Research Service Award (T32 DK07013)
- National Heart, Lung, and Blood Institute (HL146193, HL146201, HL146208, HL146240, HL146333, N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169)
- French Ministry of Health (AOM 09114, INSERM AO 8022LS)
- Agence de la Biomedecine (R0 8156LL)
- AURA and Roche (2009-152-447G)
- JDRF (17-2012-377)
- National Institute on Aging (P30-AG-02482, P30-AG-08808)
- Kaiser Permanente (NIH/NCRR UCSF-CTSI UL1 RR-024131)
- Merck
- Canadian Institutes of Health Research ((#DCT 14281)
- National Center for Research Resources General Clinical Research Center (RR000032, RR000039, RR00585, RR23940)
- National Center for Health Statistics
- University of Minnesota General Clinical Research Center
- National Institute of Diabetes and Digestive and Kidney Diseases (1R01DK116790, DK056943, DK056956, DK056957, DK056961, DK090728, DK106912, DK51975, N01-DK-6-2285, N01-DK-7-2291, P30-DK-020572, P30-DK-036836, R01 DK113111, R01-DK082447, R01DK097020, R01DK119199, R03-DK-094484, R34-DK-097808, U01 DK045388, U01 DK053869, U01 DK066013, U01 DK094157, U01 DK094176, U01 DK35073, U01DK060902, U01DK060963, U01DK060980, U01DK060984, U01DK060990, U01DK061021, U01DK061022, U01DK061028, U24DK060990, UC4-DK-101108, UL1-TR-002494)
- National Institute on Minority Health and Health Disparities (M01 RR00071)
- National Center for Advancing Translational Sciences (M01 RR-16500, P20 GM109036, RR024150, RR024153, RR025008, RR025777, RR033179, TR000001, TR000005, TR000135, TR000165, TR000454, TR001417, UL1 RR025752, UL1 RR025777, UL1 RR029887, UL1 TR-000424, UL1-TR-000040, UL1-TR-001079, UL1-TR-001105, UL1-TR-001420, UL1-TR-001422, UL1-TR-002319, UL1-TR-002319-02, UL1-TR-002556, UL1RR029879, UL1TR000003, UL1TR000433, UL1TR000439)
- U.S. Public Health Service (M01-RR00400, MO1-RR00030, MO1-RR00034, MO1-RR00036, MO1-RR00051, MO1-RR00058, MO1-RR00059, MO1-RR00425, R01-DK 39826, R01-DK 39908)
- Bristol-Myers Squibb Pharmaceutical Research Institute
- National Eye Institute
- Genetic Clinical Research Centers Program
- Topics
- Health Sciences › Medicine › Nephrology › Chronic Kidney Disease and Diabetes
- Health Sciences › Medicine › Nephrology › Acute Kidney Injury Research
- Health Sciences › Medicine › Nephrology › Dialysis and Renal Disease Management
- Keywords
- estimated glomerular filtration rate, cystatin C, serum creatinine, chronic kidney disease prevalence, Black people, kidney function estimation, CKD staging, equation validation
- MeSH terms
- Adult, Aged, Algorithms, Black or African American, Creatinine, Female, Glomerular Filtration Rate, Humans, Male, Middle Aged, United States, Black People, Racial Groups, Renal Insufficiency, Chronic, Cystatin C, Datasets as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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