In 2018, then University of Washington medical student Naomi Nkinsi, was “shocked” by the dual reporting of estimated Glomerular Filtration Rate (eGFR), which is used to assess kidney function by race, specifically African American or non-African American. Other medical students joined Nkinsi’s campaign to remove racial factors from medical calculations/algorithms. (This article uses Black, non-Hispanic for the group previously referred to as African American, but the U.S. Census continues to use both terms.)
In response, specifically to the eGFR calculation, the National Kidney Foundation (NKF) and the American Society of Nephrology (ASN) created the Task Force on Reassessing the Inclusion of Race in Diagnosing Kidney Diseases to examine the issue and provide recommendations.
In April 2021, the NKF-ASN Task Force issued an interim report.1 The interim report is the second step in a three-step process:
- Clarify the problem of race-based equations and examine the evidence to replace them.
- Review challenges relative to identifying and implementing alternative methods.
- Recommend the best approach for replacing the existing equations.
The NKF-ASN Task Force responded quickly, despite the lack of a clear understanding about the outcome of its work. It is imperative to collectively settle on a solution that best serves all patients based on data, equity, and healthcare outcomes. Nephrology is leading the charge to examine the use of variables defined by race in clinical algorithms. Similar challenges exist in other disciplines, including cardiology, cardiothoracic surgery, endocrinology, obstetrics, oncology, pulmonary medicine, and urology. Indeed, the eGFR calculation is only one of at least 13 clinical algorithms that uses a race variable.2
How did we get here?
Structural racism that affects health must be distinguished from physiological and pathophysiological determinants of health. “Black, non-Hispanic” is a social construct and not a biological one. (An example of a physiological difference is the relationship between skin pigmentation and ultraviolet light absorption that is critical for vitamin D synthesis.) Binary choices based on social constructs are particularly challenging in populations where an individual’s heritage can be heterogenous. Nevertheless, observational studies identified kidney function differences based on the social construct of racial identification.
Directly measured GFR is limited to research applications. Indirect measures are more practical in routine practice, including assessment of serum creatinine and urea nitrogen that are inversely proportional to kidney function. These tests have existed for over a century and are among the most commonly performed clinical laboratory tests. In reporting results, clinical laboratories recognize differences in serum creatinine based on age and sex that may reflect, in part, differences in muscle mass; thus, age- and sex-specific reference intervals are common. As noted, observational studies also demonstrated differences based on race, but causation and how to integrate those observations into diagnoses, categorizations, and treatment were not well understood.
Clinical researchers sought a more unified approach to assess kidney function and explored algorithms that corrected for recognized differences in adults based on age and sex. The Jelliffe equation, published as a letter to the editor in 1973, used serum creatinine, a body surface factor of 1.73m2 that became embedded in subsequent equations, along with age and sex. Another early proposed equation that gained utility was the Cockcroft–Gault equation, based on data from 249 white males that measured creatinine clearance ranging from 30 to 130 mL/min. The equation assumed women have 85% of the kidney function of men without any direct data from the original all male cohort. The empirical correction factor for females was later validated to be between 84% and 88% of the male value. Subsequent research, including the Third National Health and Nutrition Examination Survey (NHANES), found that the Cockcroft–Gault equation may be insufficient in Black, non-Hispanic individuals because of higher serum creatinine in Black, non-Hispanic adults compared to White, non-Hispanic, adults.
Recognizing these shortcomings, clinical researchers added a race coefficient to address the observation that patients who self-identified as African American had significantly higher eGFR values compared to the gold-standard of directly measured GFR — leading to the Modification of Diet in Renal Disease (MDRD) Study equation. Despite no inherent physiological difference, race was used as a substitute for unidentified factor(s) that are more common in people who self-identify as Black, non-Hispanic. Importantly, the African American coefficient in the regression models in the MDRD Study equation was a statistically significant improvement when compared to the standard of directly measured GFR. The MDRD Study equation was further validated in the African American Study of Kidney Disease. Andrew Levey, then editor of the American Journal of Kidney Disease, was instrumental in promoting the MDRD Study equation as reflective of the observational differences. The dual race-based eGFR reporting became and remains a cornerstone in the International Kidney Disease: Improving Global Outcomes (KDIGO) and US. Kidney Disease Outcomes Quality Initiative (KDOQI) clinical practice guidelines.
Discussion ensued as to the underlying cause for observed racial differences. Years later, the original investigators updated the analysis; the equation known as the CKD-EPI creatinine equation still included a race coefficient.3 This revision was based on analysis of pooled data from 10 studies and included almost 3,000 patients who self-identified as Black, non-Hispanic. The CKD-EPI coefficient for African Americans compared to non-African Americans was 1.16 versus 1.21 in the MDRD Study equation.3 (The higher eGFR when using the race coefficient suggests “more normal” kidney function in Black, non-Hispanic adults than in matched non-African Americans for identical serum creatinine and age/sex.)
Where are we now?
Black, non-Hispanic adults are three times more likely to suffer from kidney failure; they constitute over 35% of U.S. dialysis patients yet comprise only 13% of the U.S. Census population. Given that Black, non-Hispanic adults have higher rates of kidney failure, delays in care due to under-estimation of risk would exacerbate this gap. With dual eGFR reporting, Black, non-Hispanics have delayed referral to nephrologists. Indeed, in a cohort study that compared eGFR calculated with and without the race coefficient, achieving a clinical threshold for kidney transplant referral and eligibility was delayed because of the higher eGFR calculated for Black, non-Hispanic individuals.4,5 However, proponents of the CKD-EPI creatinine equation point out that ignoring the observed differences between African American and non-African American eGFR data would lead to over-diagnosis and over-treatment.6 Specifically, eliminating the race coefficient is associated with a systematic error in the evaluation of Black, non-Hispanic adults by underestimating reported GFR compared to direct measurement of GFR throughout the range of values.
The observed renal differences based on race impact other aspects of nephrology; they are not limited to the eGFR equation. The Kidney Donor Risk Index (KDRI), implemented by the National Kidney Allocation System in 2014, summarizes the likelihood of graft failure after deceased-donor kidney transplant. It includes a factor for race. The inclusion of this factor is based on the empirical observation that Black donors’ kidneys perform worse than non-Black donors’ kidneys, regardless of the recipient’s race. Genetic factors (e.g., the Apolipoprotein L1 gene [APOL1]) could replace race in KDRI; however, current turnaround times make implementation challenging because of need to provide test results to inform transplant center decision-making during the finite hours that a deceased person’s donor kidney is viable.7
The NKF-ASN Task Force is working to quickly resolve issues related to the inclusion of race in eGFR and other calculations. It is prudent to await their final report before implementing widespread changes, because some already-suggested approaches are confusing and potentially misleading.8,9 Clinical laboratories dropping the African American eGFR coefficient before the final report could be unresponsive to the professional guidance from NKF-ASN. Already suggested options include discarding the non-African American value or providing a weighted result. Dropping only the African American value “would induce a systematic underestimation of measured GFR in Blacks, with potential unintended consequences at the individual and population levels,” Salman Ahmed and researchers wrote in an article in the Journal of General Internal Medicine.10
Mallika Mendu and colleagues examined the impact of removing the race coefficient from the CKD-EPI calculation of eGFR on how Black, non-Hispanic patients are classified.11 More than 30% of Black, non-Hispanic patients would be reclassified as having a more severe stage of CKD, with approximately 25% at stage G3 reclassified to stage G4 CKD based on eGFR. Such a change would result in the referral of many more Black, non-Hispanic patients to more advanced kidney care, e.g., specialists and potential preparation for dialysis. This shift may help some individuals appropriately receive more timely or intensive interventions; it may also lead to “over-treatment” or have unintended consequences for others. Importantly, 3.1% of Black, non-Hispanic individuals with a CKD-EPI creatinine-based eGFR of >20 mL/min/1.73m2 would meet the criteria for kidney transplant priority (eGFR <20 mL/min/1.73m2) if the race coefficient were removed. Among Black non-Hispanic patients with a CKD-EPI eGFR <20 mL/min/1.73m2, only 19.2% were referred for kidney transplantation. Thus, overcoming inequities in access to kidney transplantation cannot be entirely addressed by modifying eGFR reporting.
Vishal Duggal and colleagues found that the prevalence of CKD among U.S. Black, non-Hispanic adults would double if the race coefficient were removed. The change could affect up to 40% of Black non-Hispanics using common medications for which dose adjustments are recommended based on kidney function. Lower doses of drugs cleared by the kidneys could impact clinical outcomes if insufficient drug doses are prescribed; conversely, they could decrease drug toxicity if current dosing is excessive.12
The ultimate question may not be what eGFR equation best predicts measured GFR in different populations, but which equation leads to the best health outcomes in each biologically defined population. How can serum-based eGFR and the urinary albumin-creatinine ratio test results be applied differently based on identifiable additional risk factors, including age and sex? The Kidney Failure Risk Equation (KFRE), validated across multiple populations, is one approach. It was developed by Nav Tangri and colleagues and predicts kidney failure risk at 2 and 5 years.13 The KFRE performed well even without the race coefficient.12
Jennifer Bragg-Gresham and colleagues assessed the impact of excluding the race factor in the CKD-EPI equation using data from NHANES (1999 to 2018) and data on Black veterans from the Veterans Affairs (VA) Health System (2018).14 Based on NHANES data, the mean eGFR for Black, non-Hispanic adults decreased from 102.8 mL/min/1.73m2 with the race coefficient to 88.1 mL/min/1.73m2 without it. Using VA data, the mean eGFR decreased from 82.9 to 71.6 mL/min/1.73m2. The prevalence of eGFR <60 mL/min/1.73 m2 increased from 5.8 to 10.4% using the NHANES data and from 15.5 to 26.3% using the VA data. These changes demonstrate the magnitude of the impact that dropping the African American coefficient would have using real-world data. It is important, therefore, to understand the repercussions of any possible change before one is implemented.
Introducing a new equation without a race coefficient poses challenges, because most patients will see an eGFR that is different than the one previously reported using the CKD-EPI creatinine equation, especially near decision values. The revised calculation will meaningfully impact many individuals, including both positive and negative changes in, for example, eligibility for clinical trial enrollment, medication management (e.g., diabetes, oncology, antibiotics, anticoagulants), contrast imaging, nephrology referral, dialysis eligibility, kidney transplantation recipient and donor eligibility, medical nutrition-therapy education, and even reimbursement for health services and life insurance. W. Greg Miller notes that the eGFR calculation uncertainty has a greater impact than the race coefficient in the estimation,15 yet race-based adjustments shift patients into different categories on both an individual and population basis compared to the absence of adjustments.
Professional organizations, including the NKF are likely to provide additional guidance to clinical laboratories about how to communicate and implement the expected changes. This guidance includes whether clinical laboratories report, at least for some time, both the CKD-EPI equation values and the new eGFR value to allow clinicians to compare results. Will existing clinical trials require CKD-EPI-based calculations? Will prior studies need to be re-calibrated to reflect the new eGFR calculation?
Alternatives to race self-identification to describe meaningful underlying physiological and pathophysiological differences must be explored.16 One approach could be to identify the genetic factors that increase risk for Black, non-Hispanic individuals (e.g., apolipoprotein L1 [APOL1], a minor apoprotein component of HDL cholesterol).
APOL1 is involved in protecting against Trypanosoma brucei rhodesiense infection, a parasite transmitted by the tsetse fly that causes sleeping sickness. Two APOL1 coding sequence variants in APOL1 (G1 and G2) confer resistance to the parasite yet are associated with kidney disease. People with one variant have Trypanosoma brucei rhodesiense protection, but those with two have increased risk of kidney disease (i.e., a recessive trait). Many African Americans are descendants of people of West African nations, which have a high prevalence of APOL1 variants. For example, the Yoruba people of Nigeria have a 40% and 8% prevalence of G1 and G2 risk alleles, respectively. The G1 and G2 risk alleles are found in over 30% of African Americans. Consequently, descendants from West Africa also have a high prevalence of APOL1 risk alleles, as well as APOL1-associated kidney diseases. The risk alleles are found in nearly half (47%) of the hypertension-attributed end stage renal disease in Black, non-Hispanic individuals.
Cystatin C is a viable biomarker to complement serum creatinine and eGFR, because it is less influenced by diet and muscle mass. 17 Currently, NKF KDOQI clinical practice guidelines suggest cystatin C testing for patients with a CKD EPI creatinine-based eGFR of 45-59 mL/min/1.73m2 in the absence of significant albuminuria (if confirmed for 3+ months, CKD stage G3aA1). Given cystatin C is independent of race, this test may be an attractive alternative. There are CKD EPI equations for cystatin C, either alone or when combined with creatinine. Concerns about substituting or supplementing creatinine with cystatin C testing include higher cost, limited availability, still incomplete assay standardization, and absence of clear payer payment policies.
The clinical laboratory and nephrology communities serve critical roles in assessing kidney function. Progress with eGFR was marred with a response to observed differences between a calculated eGFR from the gold standard of measured GFR for Black, non-Hispanic individuals. The unintended consequences of including race in the calculations are impossible to ignore. Today’s heightened awareness of racial issues, with the strong voice of Nkinsi and others raising concern, brings us to the NKF-ASN Task Force and its interim report. The future final report will define a path that will exclude the race coefficient from eGFR reporting. The change will positively and negatively impact patient care. We should all await that report. When issued, laboratorians should quickly implement the recommendations to assure a unified approach to eGFR reporting. This change will not be the final chapter, because other factors (e.g., social determinants of health) influence interpretation of eGFR and CKD progression. Improving kidney disease health equity clearly requires additional interventions beyond the future race-independent eGFR calculation.
- Delgado C, Baweja M, Burrows NR, et al. Reassessing the inclusion of race in diagnosing kidney diseases: an interim report from the NKF-ASN Task Force. American Journal of Kidney Diseases 2021. In press. doi.org/10.1053/j.ajkd.2021.03.008
- Vyas DA, Eisenstein LG, Jones DS. Hidden in plain sight — reconsidering the use of race correction in clinical algorithms. N Engl J Med 2020; 383:874-882 doi: 10.1056/NEJMms2004740.
- Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate [published correction appears in Ann Intern Med. 2011;155:408] Ann Intern Med. 2009;150:604–612. doi.org/10.7326/0003-4819-150-9-200905050-00006
- Zelnick LR, Leca N, Young B. et al. Association of the estimated glomerular filtration rate with vs without a coefficient for race with time to eligibility for kidney transplant. JAMA Netw Open. 2021 Jan 4;4(1):e2034004. doi: 10.1001/jamanetworkopen.2020.34004..
- Levey AS, Tighiouart H, Titan SM, Inker LA. Estimation of glomerular filtration rate with vs without including patient race. JAMA Intern Med. 2020;180:793-795. doi: 10.1001/jamainternmed.2020.0045
- Rao PS, Schaubel DE, Guidinger MK, et al. A comprehensive risk quantification score for deceased donor kidneys: the kidney donor risk index. Transplantation. 2009;88:231-236. doi: 10.1097/tp.0b013e3181ac620b
- Julian BA, Gaston RS, Brown WM, et al. Effect of replacing race with apolipoprotein L1 genotype in calculation of Kidney Donor Risk Index. Am J Transplant. 2017;17:1540-1548. doi: 10.1111/ajt.14113
- Eneanya ND, Yang W, Reese PP. Reconsidering the consequences of using race to estimate kidney function. JAMA 2019;322:113-114. doi: 10.1001/jama.2019.5774
- Moderators: El-Khoury JM, Ovalle AA, Cervinski MA Experts: Levey AS, Jones G, Eneanya ND, et al. Is It time to move on? Reexamining race in glomerular filtration rate Equations, Clinical Chemistry. 2021;67:585-591. doi.org/10.1093/clinchem/hvaa333
- Levey AS, Titan SM, Powe NR, et al. Kidney disease, race, and GFR estimation. Clin J Am Soc Nephrol. 2020 Aug 7;15(8):1203-1212. doi: 10.2215/CJN.12791019. Epub 2020 May 11.
- Ahmed S, Examining the potential impact of race multiplier in estimated glomular filtration rate calculation on African American care outcomes. J General Internal Medicine. 2021; Feb;36(2):464-471. doi: 10.1007/s11606-020-06280-5.
- Duggal V, Thomas I, Montez-Rath ME, et al. National estimates of CKD prevalence and potential impact of estimating glomerular filtration rate without race. J Am Assoc Nephrology. May 2021 online doi: org/10.1681/ASN.2020121780
- Tangri N, Grams ME, Levey AS, et al. Multinational assessment of accuracy of equations for predicting risk of kidney failure: A meta-analysis. JAMA. 2016;315(2):164–174. doi: 10.1001/jama.2015.18202.
- Bragg-Gresham J, Zhang X, Le D, et al. Prevalence of chronic kidney disease among black individuals in the US after removal of the black race coefficient from a glomerular filtration rate estimating equation. JAMA Netw Open. 2021;4:e2035636. doi: 10.1001/jamanetworkopen.2020.35636.
- Miller WG. Uncertainty in estimated glomerular filtration rate is much larger than the race adjustment term, Clinical Chemistry. 2021;67:693-695. doi.org/10.1093/clinchem/hvab007
- Best LE, Chenault J. Racial classifications, biomarkers, and the challenges of health disparities research in the African diaspora J Pan Afr Stud. 2014;7:74-98. PMID: 30270981; PMCID: PMC6162056.
- Inker LA, Schmid CH, Tighiouart H, et al. CKD-EPI Investigators: Estimating glomeruler filtration rate from serum creatine and cystatin C [published correction appears in N Engl J Med. 2012;367: 2060]. N Engl J Med. 2021;367: 20-29.