Association of the Estimated Glomerular Filtration Rate With vs Without a Coefficient for Race With Time to Eligibility for Kidney Transplant

Abstract

This cohort study assesses the association between estimated glomerular filtration rate (eGFR) calculated with vs without a coefficient for race and time to achievement of an eGFR less than 20 mL/min/1.73 m ².

Key Points

Question

Is adjusting for Black race in estimating equations for glomerular filtration rate in patients with chronic kidney disease associated with a delay in kidney transplant eligibility?

Findings

In this cohort study of 1658 self-identified Black adults with chronic kidney disease, commonly used estimates of kidney function did not correspond well with directly measured kidney function. Estimating kidney function not including a coefficient for race (vs including a race coefficient) was significantly associated with a shorter time to achieving an estimated glomerular filtration rate less than 20 mL/min/1.73 m ², a key threshold of kidney function for referral and listing for kidney transplant.

Meaning

The findings suggest that biases in race-based glomerular filtration rate estimates may be associated with delays in potential kidney transplant eligibility.

Abstract

Importance

Kidney transplant is associated with improved survival and quality of life among patients with kidney failure; however, significant racial disparities have been noted in transplant access. Common equations that estimate glomerular filtration rate (eGFR) include adjustment for Black race; however, how inclusion of the race coefficient in common eGFR equations corresponds with measured GFR and whether it is associated with delayed eligibility for kidney transplant listing are unknown.

Objective

To compare eGFR with measured GFR and evaluate the association between eGFR calculated with vs without a coefficient for race and time to eligibility for kidney transplant.

Design, Setting, and Participants

This prospective cohort study used data from the Chronic Renal Insufficiency Cohort, a multicenter cohort study of participants with chronic kidney disease (CKD). Self-identified Black participants from that study were enrolled between April 2003 and September 2008, with follow-up through December 2018. Statistical analyses were completed on November 11, 2020.

Exposure

Estimated GFR, measured annually and estimated using the creatinine-based Chronic Kidney Disease-Epidemiology (CKD-EPI) equation with and without a race coefficient.

Main Outcomes and Measures

Iothalamate GFR (iGFR) measured in a subset of participants (n = 311) and time to achievement of an eGFR less than 20 mL/min/1.73 m ², an established threshold for kidney transplant referral and listing.

Results

Among 1658 self-identified Black participants, mean (SD) age was 58 (11) years, 848 (51%) were female, and mean (SD) eGFR was 44 (15) mL/min/1.73 m ². The CKD-EPI eGFR with the race coefficient overestimated iGFR by a mean of 3.1 mL/min/1.73 m ² (95% CI, 2.2-3.9 mL/min/1.73 m ²; P < .001). The mean difference between CKD-EPI eGFR without the race coefficient and iGFR was of smaller magnitude (−1.7 mL/min/1.73 m ²; 95% CI, −2.5 to −0.9 mL/min/1.73 m ²). For participants with an iGFR of 20 to 25 mL/min/1.73 m ², the mean difference in eGFR with vs without the race coefficient and iGFR was 5.1 mL/min/1.73 m ² (95% CI, 3.3-6.9 mL/min/1.73 m ²) vs 1.3 mL/min/1.73 m ² (95% CI, −0.3 to 2.9 mL/min/1.73 m ²). Over a median follow-up time of 4 years (interquartile range, 1-10 years), use of eGFR calculated without vs with the race coefficient was associated with a 35% (95% CI, 29%-41%) higher risk of achieving an eGFR less than 20 mL/min/1.73 m ² and a shorter median time to this end point of 1.9 years.

Conclusions and Relevance

In this cohort study, inclusion of the race coefficient in the estimation of GFR was associated with greater bias in GFR estimation and with delayed achievement of a clinical threshold for kidney transplant referral and eligibility. These findings suggest that nephrologists and transplant programs should be cautious when using current estimating equations to determine kidney transplant eligibility.