New Creatinine- and Cystatin C–Based Equations to Estimate GFR without Race,The New England Journal of Medicine

当前位置： X-MOL 学术 › N. Engl. J. Med. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

New Creatinine- and Cystatin C–Based Equations to Estimate GFR without Race
The New England Journal of Medicine ( IF 158.5 ) Pub Date : 2021-09-23 , DOI: 10.1056/nejmoa2102953
Lesley A Inker ₁ , Nwamaka D Eneanya ₁ , Josef Coresh ₁ , Hocine Tighiouart ₁ , Dan Wang ₁ , Yingying Sang ₁ , Deidra C Crews ₁ , Alessandro Doria ₁ , Michelle M Estrella ₁ , Marc Froissart ₁ , Morgan E Grams ₁ , Tom Greene ₁ , Anders Grubb ₁ , Vilmundur Gudnason ₁ , Orlando M Gutiérrez ₁ , Roberto Kalil ₁ , Amy B Karger ₁ , Michael Mauer ₁ , Gerjan Navis ₁ , Robert G Nelson ₁ , Emilio D Poggio ₁ , Roger Rodby ₁ , Peter Rossing ₁ , Andrew D Rule ₁ , Elizabeth Selvin ₁ , Jesse C Seegmiller ₁ , Michael G Shlipak ₁ , Vicente E Torres ₁ , Wei Yang ₁ , Shoshana H Ballew ₁ , Sara J Couture ₁ , Neil R Powe ₁ , Andrew S Levey ₁ ,

Affiliation

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.).

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

In 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.

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.)

中文翻译：

基于肌酐和胱抑素 C 的新方程可在不存在种族的情况下估算 GFR

背景

目前使用血清肌酐或胱抑素 C 估计肾小球滤过率 (eGFR) 的方程结合了年龄、性别和种族来估计测量的 GFR。然而，eGFR 方程中的种族是一种社会结构，而不是生物学结构。

方法

我们使用来自两个开发数据集的数据开发了新的 eGFR 方程，不包含种族：10 项研究（8254 名受试者，31.5% 黑人）针对血清肌酐，13 项研究（5352 名受试者，39.7% 黑人）针对血清肌酐和胱抑素 C。通过 12 项研究的数据集（4050 名参与者，14.3% 黑人），我们将新的 eGFR 方程与测量的 GFR 的准确性进行了比较。我们使用当前和新的方程预测了美国成年人样本中慢性肾脏病 (CKD) 的患病率和 GFR 阶段。

结果

在验证数据集中，当前使用年龄、性别和种族的肌酐方程高估了黑人测量的 GFR（中位数，每 1.73 m 2^体表面积每分钟 3.7 ml；95% 置信区间 [CI]，1.8 至5.4），非黑人的程度较小（中位数，每分钟每 1.73 m ² 0.5 ml ；95% CI，0.0 至 0.9）。当当前的 eGFR 方程中省略对黑人种族的调整时，黑人的测量 GFR 被低估（中位数，每 1.73 m ²每分钟 7.1 ml ；95% CI，5.9 至 8.8）。^{使用年龄和性别并忽略种族的新方程低估了黑人的测量 GFR（中位数，每 1.73 m 2} 3.6 毫升；95% CI，1.8 至 5.5），高估了非黑人的测量 GFR（中位数，3.9 毫升每分钟）每 1.73 m ²；95% CI，3.4 至 4.4）。对于所有方程，黑人和非黑人 85% 或更多的 eGFR 在测量的 GFR 的 30% 范围内。不考虑种族的新肌酐-半胱氨酸蛋白酶抑制剂 C 方程比新肌酐方程更准确，种族组之间的差异更小。与当前的肌酐方程相比，新的肌酐方程（而非新的肌酐-半胱氨酸蛋白酶抑制剂 C 方程）增加了黑人 CKD 患病率的人群估计值，并且非黑人中的患病率相似或更低。