A Step Toward Health Equity for Veterans: Evidence Supports Removing Race From Kidney Function Calculations
Background: The practice of race-based medicine fails to recognize that race cannot be used as a proxy for genetic ancestry and that racial and ethnic categories are complex sociopolitical constructs without biological basis. Clinical algorithms and equations that incorporate race modifiers and are currently considered standard for diagnosis and management of disease are appropriately being scrutinized for lack of biological plausibility and their role in exacerbating health inequities. In this paper, we review the history, evidence, and implications of using a Black race coefficient when calculating estimated glomerular filtration rate (eGFR) in the diagnosis and management of kidney disease.
Observations: Currently, the US Department of Veterans Affairs (VA) uses the Modification of Diet in Renal Disease (MDRD) equation for eGFR. This equation includes a Black race coefficient that results in an eGFR that is 21% higher for a Black patient when compared with a patient of any other race. The rationale for the inclusion of this coefficient is based on racist science that incorrectly assumes race as a proxy for genetic ancestry. Multiple studies across diverse Black populations demonstrate that the application of a race coefficient in kidney function estimation equations is inferior when compared with the race-neutral option. Furthermore, the most utilized eGFR equations are biased and imprecise. Because eGFR is the primary diagnostic method for detecting and managing kidney disease, preventing its progression, planning for dialysis, and evaluating for transplantation, it is vital that eGFR be as accurate, precise, and equitable as possible.
Conclusions: The incorporation of a race coefficient in kidney estimation equations lacks biological plausibility and its use exacerbates kidney health disparities. Until a better method to estimate kidney function becomes available, a race-neutral option for current estimation equations should be applied for all patients.
In a VA medical center study, although Black patients were referred to nephrology care at higher rates than White patients, Black patients had faster progression to CKD stage 5.13 An earlier study showed that, at any given eGFR, Black patients have higher levels of albuminuria compared to White patients.14 While the reasons behind this observation are likely complex and multifactorial, one hypothesis is that Black patients were already at a more advanced stage of kidney disease at the time of referral as a result of the overestimation of eGFR calculations related to the use of a race coefficient.
Additionally, numerous analyses have revealed that Black patients are less likely to be identified as transplant candidates, less likely to be referred for transplant evaluation and, once on the waiting list, wait longer than do White patients.11,15
Estimated Glomerular Filtration Rate
It is imperative that clinicians have the most accurate measure of GFR to ensure timely diagnosis and appropriate management in patients with CKD. The gold standard for determining renal function requires measuring GFR using an ideal, exogenous, filtration marker such as iothalamate. However, this process is complex and time-consuming, rendering it infeasible in routine care. As a result, we usually estimate GFR using endogenous serum markers such as creatinine and cystatin C. Due to availability and cost, serum creatinine (SCr) is the most widely used marker for estimating kidney function. However, many pitfalls are inherent in its use, including the effects of tubular secretion, extrarenal clearance, and day-to-day variability in creatinine generation related to muscle mass, diet, and activity.16 The 2 most widely used estimation equations are the Modification of Diet in Renal Disease (MDRD) study equation and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equation; both equations incorporate correction factors for age, sex, and race.
The VA uses MDRD, which was derived and validated in a cohort of 1628 patients that included only 197 Black patients (12%), resulting in an eGFR for Black patients that is 21% higher than is the eGFR for non-Black patients with the same SCr value.9 In the VA electronic health record, the race coefficient is incorporated directly into eGFR laboratory calculations based on the race that the veteran self-identified during intake. Because the laboratory reports only a race-adjusted eGFR, there is a lack of transparency as many health care providers and patients are unaware that a race coefficient is used in eGFR calculations at the VA.
Case for Removing Race Coefficient
When applied to cohorts outside the original study, both the MDRD and CKD-EPI equations have proved to be highly biased, imprecise, and inaccurate when compared to measured GFR (mGFR).15,17 For any given eGFR, the possible mGFR may span 3 stages of CKD, underscoring the limitations of using such a crude estimate in clinical decision making.17
Current Kidney Estimation Pitfalls
A recent cohort study by Zelnick and colleagues that included 1658 self-identified Black adults showed less bias between mGFR and eGFR without the use of a race coefficient, and a shorter median time to transplant eligibility by 1.9 years.15 This study provides further evidence that these equations were derived from a biased observational data set that overestimates eGFR in Black patients living with CKD. This overestimation is particularly egregious for frail or malnourished patients with CKD and multiple comorbidities, with many potential harmful clinical consequences.
In addition, multiple international studies in African countries have demonstrated worse performance of eGFR calculations when using the race coefficient than without it. In the Democratic Republic of the Congo, eGFR was calculated for adults using MDRD with and without the race coefficient, as well as CKD-EPI with and without the race coefficient, and then compared to mGFR. Both the MDRD and the CKD-EPI equations overestimated GFR when using the race coefficient, and notably the equations without the race coefficient had better correlation to mGFR.18 Similar data were also found in studies from South Africa, the Ivory Coast, Brazil, and Europe.19-22
