The estimation of glomerular filtration rate (GFR) is usually indirectly calculated from serum creatinine in routine clinical practice. This indirect estimated GFR (eGFR) determination is then used to perform therapeutic decisions. However, serum creatinine may be influenced not only by GFR, but also by muscle mass and diet, therefore age, sex, race [Black/African American (AA) versus other], height and weight have been used to adjust the eGFR [1]. While age, sex or height are biological variables, race/ethnicity certainly has a biological/genetic background but also carries a strong social and psychological burden and is usually a very sensitive topic. As a consequence, many medical centres have removed the race adjustment from eGFR despite the lack of studies assessing the potential clinical impact of this decision [2, 3].
The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation to estimate GFR from serum creatinine was developed and validated across 10 studies including people with and without chronic kidney disease (CKD). The race was classified as AA or other as assigned by the study participants or the investigators [1]. A reassessment of the original CKD-EPI equation excluding the adjustment for race has led to a systematic error in the evaluation of AA participants, leading to an underestimation of the measured GFR and a worse performance of the CKD-EPI equation [4–6]. New eGFR equations that omit race but incorporate both creatinine and cystatin C in the equation have been found to be more accurate [7].
Given the potential implications of removing race from the CKD-EPI eGFR equation, we aim to replicate previous findings in a broad population of patients with a high cardiovascular and renal risk, including type 2 diabetes in the Action to Control Cardiovascular Risk in Diabetes (ACCORD; NCT00000620) trial, hypertension without diabetes in the Systolic Blood Pressure Intervention Trial (SPRINT; NCT01206062) and heart failure with preserved ejection fraction in the Aldosterone Antagonist Therapy for Adults with Heart Failure and Preserved Systolic Function (TOPCAT; NCT00094302) trial.
We computed eGFR from serum creatinine using the CKD-EPI equation with and without the race indicator for AA/Black patients. We then compared the distributional eGFR shift, CKD reclassification and prognostic implications of calculating eGFR with and without race.
ACCORD enrolled 10 251 patients, of whom 1947 (19%) were Black/AA. The inclusion of race adjustment in the CKD-EPI equation gave a mean eGFR of 87 ± 19 mL/min/1.73 m2. When race was excluded from the equation, the mean eGFR was 75 ± 17 mL/min/1.73 m2, i.e. a difference of −12 ± 3 mL/min/1.73 m2 by excluding race from the equation (Figure 1A). Excluding race from the CKD-EPI equation more than doubled the number of patients classified as having CKD Stage 3: 378 excluding race versus 166 including race. A similar pattern was seen in SPRINT and TOPCAT. In SPRINT, 9361 patients were included, of whom 2928 (31%) were Black/AA. Excluding race from the equation led to a difference of −10 ± 3 mL/min/1.73 m2, with many more patients classified as having CKD Stage 3 (680 versus 1048) (Figure 1B). In TOPCAT-Americas, 1767 patients were included, of whom 293 (17%) were Black/AA. Excluding race from the equation led to a difference of −8 ± 3 mL/min/1.73 m2 and more patients classified as having CKD Stage 3 (187 versus145) (Figure 1C).
FIGURE 1:
Influence of race in the estimation of GFR. Calculating eGFR without the inclusion of the race variable (‘African American’) leads to a leftward shift in eGFR, i.e. AA patients have their eGFR underestimated, which may have major implications for treatment, follow-up and prognostic assessment. (A) ACCORD, (B) SPRINT and (C) TOPCAT. We used the CKD-EPI formula to compute eGFR, hence these results may differ from those presented in the respective trials using the Modification of Diet in Renal Disease formula.
In this study, excluding race from the CKD-EPI equation systematically led to an underestimation of GFR and classified more patients as having worse CKD stages. These findings have important clinical implications and potential unintended consequences, as Black/AA patients could have received lower drug doses or have a label contraindication for taking certain drug and some could have been excluded from these trials based on low eGFR.
Our findings expand to high CV risk patients’ previous reports [4–8], which led a National Kidney Foundation–American Society of Nephrology task force to recommend immediate implementation of the new CKD-EPI creatinine equation refit without the race variable [7, 9].
Further research on GFR estimation aimed at eliminating race and ethnic disparities is warranted.
CONFLICT OF INTEREST STATEMENT
The authors have no potential conflicts of interest regarding the content of this article.
Contributor Information
João Pedro Ferreira, Unidade de Investigaçao Cardiovascular, Faculdade de Medicina Universidade do Porto, Porto, Portugal; Centre d'Investigations Cliniques Plurithématique 1433 and Inserm U1116, CHRU, FCRIN INI-CRCT, Université de Lorraine, Nancy, France.
Faiez Zannad, Centre d'Investigations Cliniques Plurithématique 1433 and Inserm U1116, CHRU, FCRIN INI-CRCT, Université de Lorraine, Nancy, France.
Scott D Solomon, Cardiovascular Division Brigham and Women's Hospital, Boston, MA, USA.
Bertram Pitt, University of Michigan School of Medicine, Ann Arbor, MI, USA.
Patrick Rossignol, Centre d'Investigations Cliniques Plurithématique 1433 and Inserm U1116, CHRU, FCRIN INI-CRCT, Université de Lorraine, Nancy, France.
REFERENCES
- 1. Levey AS, Stevens LA, Schmid CH et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009; 9: 604–612 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Eneanya ND, Yang W, Reese PP. Reconsidering the consequences of using race to estimate kidney function. JAMA 2019; 322: 113–114 [DOI] [PubMed] [Google Scholar]
- 3. 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] [PubMed] [Google Scholar]
- 4. Levey AS, Tighiouart H, Titan SM et al. Estimation of glomerular filtration rate with vs without including patient race. JAMA Intern Med 2020; 180: 793–795 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Diao JA, Wu GJ, Taylor HA et al. Clinical implications of removing race from estimates of kidney function. JAMA 2021; 325: 184–186 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Hsu CY, Yang W, Parikh RV et al. Race, genetic ancestry, and estimating kidney function in CKD. N Engl J Med 2021; 385: 1750–1760 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Inker LA, Eneanya ND, Coresh J et al. New creatinine- and cystatin C-based equations to estimate GFR without race. N Engl J Med 2021; 385: 1737–1749 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Levey AS, Titan SM, Powe NR et al. Kidney disease, race, and GFR estimation. Clin J Am Soc Nephrol 2020; 15: 1203–1212 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Delgado C, Baweja M, Crews DC et al. A unifying approach for GFR estimation: recommendations of the NKF-ASN task force on reassessing the inclusion of race in diagnosing kidney disease. Am J Kidney Dis 2021; 32: 2994–3015 [DOI] [PMC free article] [PubMed] [Google Scholar]