Cited by 4,695Chronic Kidney Disease and DiabetesAcute Kidney Injury ResearchDialysis and Renal Disease Management

New creatinine- and cystatin C-based equations to estimate GFR without race

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Inker, Lesley A., Eneanya, Nwamaka D., Coresh, Josef, Tighiouart, Hocine, Wang, Dan, Sang, Yingying, Crews, Deidra C., Doria, Alessandro +25 more·2021·New England Journal of Medicine

Abstract

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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Research works printed but not linked: 2

  1. [12]Warren E, Booker C, Wyden R, Lee B. Agency for Healthcare Research and Quality (AHRQ) requesting a review of the use of race-based clinical algorithms in standard medical practices Washington, DC: U.S. Congress, September 22, 2020.
  2. [33]National Kidney Foundation, American Society of Nephrology. Removing race from estimates of kidney function March 9, 2021 (https://www.asn-online.org/about/press/releases/ASN_PR_20210309_Press_release_NKF_A.pdf).

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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)
Venue
New England Journal of Medicine
Published
2021-11-04
Volume
385
Issue
19
Pages
1737-1749
ISSN
  • 0028-4793 (ISSN-L)
  • 1533-4406
OpenAlex
W3201595862
Cited by
4,695
References
34
Citations by year
2026: 1301 · 2025: 1222 · 2024: 1008 · 2023: 729 · 2022: 394 · 2021: 33 · 2014: 1 · 2013: 1 · 2012: 1
FWCI
373.01
Type
journal article
Language
en
Open access
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

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