This post is part of a collaboration between AACC Academy and SYCL, to highlight the excellent work being done by young laboratorians, and the knowledge and perspectives they bring to the laboratory community.

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). Unfortunately, GFR cannot be measured directly, so laboratory-based methods for GFR quantification have been developed. The most commonly used laboratory-based method is calculation of an estimated GFR (eGFR).

Current guidelines recommend the use of the creatinine-based Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations to measure eGFR (2). These equations incorporate four patient-specific variables: serum or plasma creatinine concentration, age, gender (male or female) and race (Black or white/other) (3). Gender and age are 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, a female’s 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 (4). Use of a race coefficient of 1.159 is recommended in the CKD-EPI equation for Black individuals due to evidence of increased serum creatinine concentrations compared to patients of white/other races (3). So, in matched white and Black patients with identical serum creatinine concentrations, age, and gender, eGFR will be increased for 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 mGFR 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 (4). This finding was reasoned with the claim that Black persons have increased lean body mass compared to white persons, referencing three studies in support (4). Combined, the three referenced studies comprised only 176 Black children and adults (6-8). Certainly we can agree that greater powered studies are necessary before applying this claim to the broader population of all Black persons. Furthermore, each study was tangentially related to lean body mass. Patient cohorts used to develop the creatinine-based CKD-EPI equations demonstrated greater diversity (Black = 10-32%, Hispanic = 2-5%, Asian = 1-2%), but there were no additional studies supporting the claim of increased lean body mass in Black individuals (3).

Race factor was implemented as a binary variable, meaning clinicians must choose between eGFR for “Black” or “white/other” patients. The reality is that racial populations are diverse and cannot be represented by two groups. For example, past 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 (9). Further, not all providers will discuss race with their patients and may make assumptions based on visual appearance, potentially resulting in inaccurate results.

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 lean body mass among individuals, but there is no biological basis for the social construct that we have termed “race”. A better tool would be measurement of lean body mass to use in eGFR equations, but this is not a trivial task. Alternatively, cystatin C-based eGFR equations could be used. Cystatin C is produced by all nucleated cells and not influenced by lean body mass, and there is a cystatin C CKD-EPI equation. Cystatin C is a far more expensive assay than creatinine, though, and is not widely available or standardized across clinical laboratories in the United States.

On March 9th, 2021 the National Kidney Foundation (NKF) and American Society of Nephrology (ASN) released a joint statement denouncing the use of a Black race coefficient stating, “The leaders of NKF and ASN agree that 1) race modifiers should not be included in equations to estimate kidney function and 2) current race-based equations should be replaced by a suitable approach that is accurate, inclusive, and standardized in every laboratory in the United States” (10).

REFERENCES

  1. Eneanya ND, Yang W, Reese PP. Reconsidering the consequences of using race to estimate kidney function. JAMA 2019;322:113-4.
  2. Inker LA, Astor BC, Fox CH, Isakova T, Lash JP, Peralta CA, et al. 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.
  3. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, 3rd, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009;150:604-12.
  4. 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.
  5. Klahr S, Levey AS, Beck GJ, Caggiula AW, Hunsicker L, Kusek JW, Striker G. The effects of dietary protein restriction and blood-pressure control on the progression of chronic renal disease. Modification of diet in renal disease study group. N Engl J Med 1994;330:877-84.
  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. 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
  10. National Kidney Foundation. Removing race from estimates of kidney function. https://www.kidney.org/news/removing-race-estimates-kidney-function (Accessed March 2021).