Why should we eliminate the Black race coefficient from eGFR equations?

The following post was written to update a previous Short that was removed because the information was outdated. Below, please see the most relevant and up-to-date information on this topic.

Glomerular filtration rate (GFR) is a measure of kidney function that quantifies total combined nephron filtration rate. GFR is used by clinicians for many purposes: to prognosticate and stage chronic kidney disease (CKD), to determine safety and dosage of clinical therapies, and to refer patients to nephrology for specialized treatment and transplant (1). GFR can be measured directly by calculating urinary clearance of intravenously administered exogenous substances (termed mGFR), but this is time consuming, complicated, and not suitable for routine patient care. The most commonly used method for GFR quantification is an indirect, laboratory-based calculation of estimated GFR (eGFR).

Current KDIGO (2012) and KDOQI (2014) guidelines recommend the use of the 2009 creatinine-based Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI_creat) equations to measure eGFR (2, 3). These equations incorporate four patient-specific variables: serum or plasma creatinine concentration, age, gender (male or female) and race (Black or non-Black) (4). Gender and age were incorporated to correct for differences in muscle mass among patients, as creatinine concentrations are directly proportional to muscle mass. For example, in male and female patients with matching serum creatinine concentrations, female eGFR will be decreased due to assumed lower baseline serum creatinine concentrations (i.e. decreased lean body mass) as compared to males. The race variable was added to eGFR equations for the same reason (5). Use of a race coefficient of 1.159 was recommended in the 2009 CKD-EPI_creat equations for Black individuals due to evidence of increased serum creatinine concentrations compared to non-Black patients (4) . So, in matched non-Black and Black patients with identical serum creatinine concentrations, age, and gender, eGFR would be increased in Black patients due to use of this race coefficient.

There are two important questions to ask to understand whether a Black race coefficient is necessary: 1) What evidence is available regarding increased serum creatinine for individuals of Black race? 2) Can race be interpreted using binary variables?

The first eGFR equations to include a race variable were published in 1999 and derived from the Modification of Diet and Renal Disease (MDRD) study cohort, a study which sought to identify the effect of low protein diet and/or antihypertensives on CKD progression (5) . While no significant associations were found, researchers now had a large study population with paired measurements of serum creatinine and m[KT1][FC([2] GFR which they utilized to optimize eGFR equations. These were termed the MDRD study equations. Within the MDRD cohort (n = 1628; white = 1304, Black = 197), researchers observed that Black individuals were found to have significantly increased serum creatinine as compared to white individuals (5). This finding was reasoned with the claim that Black persons have increased lean body mass, referencing three studies in support (5). Combined, the studies comprised only 176 Black children and adults, and were only tangentially related to lean body mass (6-8). Patient cohorts used to develop the CKD-EPI_creat were more diverse (n = 12,150; Black = 10-32%, Hispanic = 2-5%, Asian = 1-2%) but cited no additional support of the claim of increased lean body mass in Black individuals (4). Further, recent studies that have attempted to define non-GFR determinants of creatinine (i.e. BMI, BSA, height, weight, and bioelectrical impedance analysis) found that associations between Black race and GFR persist even when corrected for, and correlate best with proportion of African ancestry (9).

Race factor was implemented as a binary variable, meaning clinicians must choose between eGFR for Black or non-Black patients. The reality is that racial populations are diverse and cannot be represented by two groups. For example, past US president Barack Obama is mixed race with a Black father and white mother. So, should his clinician use a race coefficient to calculate eGFR? Mixed race populations are the fastest growing in the United States and do not fit the binary algorithm proposed over 20 years ago (10). Moreover, not all providers will discuss race with their patients and may make assumptions based on visual appearance, resulting in inaccurate GFR estimation.

The possible benefits of a race coefficient may not outweigh the possible harm. The clinical impact of overestimated GFR include limited access to specialized, nephrology care and exclusion from receipt of kidney transplantation. The race coefficient attempts to make up for differences in creatinine concentrations among individuals, but there is no biological basis for the social construct that we have termed “race”.

In response to nationwide demands to reassess the use of race in clinical algorithms, the National Kidney Foundation (NKF) and the American Society of Nephrology (ASN) formed a joint task force in July 2020 (NKF-ASN Task Force) to re-evaluate the use of race in eGFR equations. The task force evaluated 26 potential approaches for GFR estimation and published final recommendations in September 2021 (11, 12). The recommendations are as follows: 1) Immediate implementation of the 2021 CKD-EPI creatinine equation refit (CKD-EPIcr_R) without the race variable (13), 2) Increased routine use of cystatin C as a confirmatory method, especially in adults who are at risk for CKD, and 3) Increased research efforts and funding to identify new markers of eGFR. Further considerations recommended by the task force include discontinuation of the Jaffe reaction, reporting eGFR indexed to standard body surface area, and emphasizing the importance of albuminuria assessment. As clinical laboratorians, we play a critical role in ensuring swift and unified adoption of NKF-ASN recommendations to provide equitable patient care to all.

REFERENCES

1. Eneanya ND, Yang W, Reese PP. Reconsidering the consequences of using race to estimate kidney function. JAMA 2019;322:113-4.
2. Kidney disease: improving global outcomes (KDIGO) CKD work group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl 2013;3:1-150.
3. Inker LA, Astor BC, Fox CH, Isakova T, Lash JP, Peralta CA, Kurella Tamura M, Feldman HI. KDOQI US commentary on the 2012 KDIGO clinical practice guideline for the evaluation and management of CKD. Am J Kidney Dis 2014;63:713-35.
4. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, 3rd, Feldman HI, Kusek JW, Eggers P, Van Lente F, Greene T, Coresh J. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009;150:604-12.
5. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of diet in renal disease study group. Ann Intern Med 1999;130:461-70.
6. Cohn SH, Abesamis C, Zanzi I, Aloia JF, Yasumura S, Ellis KJ. Body elemental composition: comparison between black and white adults. Am J Physiol 1977;232:E419-22.
7. Harsha DW, Frerichs RR, Berenson GS. Densitometry and anthropometry of black and white children. Hum Biol 1978;50:261-80.
8. Worrall JG, Phongsathorn V, Hooper RJ, Paice EW. Racial variation in serum creatine kinase unrelated to lean body mass. Br J Rheumatol. 1990;29:371-3.
9. Hsu CY, Yang W, Parikh RV, Anderson AH, Chen TK, Cohen DL, He J, Mohanty MJ, Lash JP, Mills KT, Muiru AN, Parsa A, Saunders MR, Shafi T, Townsend RR, Waikar SS, Wang J, Wolf M, Tan TC, Feldman HI, Go AS. Race, genetic ancestry, and estimating kidney function in CKD. N Engl J Med 2021;385:1750-60.
10. US Census Bureau. Summary of modified race and census 2010 race distributions for the united states. https://www2.census.gov/programs-surveys/popest/data sets/2010/modified-race-data-2010/us-mr2010-01.xls
11. Delgado C, Baweja M, Crews DC, Eneanya ND, Gadegbeku CA, Inker LA, Mendu ML, Miller WG, Moxey-Mims MM, Roberts GV, St Peter WL, Warfield C, Powe NR. A unifying approach for GFR estimation: recommendations of the NKF-ASN task force on reassessing the inclusion of race in diagnosing kidney disease. [Epub ahead of print] Am J Kidney Dis September 23, 2021 as doi: 10.1053/j.ajkd.2021.08.003.
12. Delgado C, Baweja M, Crews DC, Eneanya ND, Gadegbeku CA, Inker LA, Mendu ML, Miller WG, Moxey-Mims MM, Roberts GV, St Peter WL, Warfield C, Powe NR. A unifying approach for GFR estimation: recommendations of the NKF-ASN task force on reassessing the inclusion of race in diagnosing kidney disease. J Am Soc Nephrol 2021;32:2994-3015.
13. Inker LA, Eneanya ND, Coresh J, Tighiouart H, Wang D, Sang Y, Crews DC, Doria A, Estrella MM, Froissart M, Grams ME, Greene T, Grubb A, Gudnason V, Gutierrez OM, Kalil R, Karger AB, Mauer M, Navis G, Nelson RG, Poggio ED, Rodby R, Rossing P, Rule AD, Selvin E, Seegmiller JC, Shlipak MG, Torres VE, Yang W, Ballew SH, Couture SJ, Powe NR, Levey AS. New creatinine- and cystatin C-based equations to estimate GFR without race. N Engl J Med 2021;385:1737-49.