Evaluation of Race-Neutral Glomerular Filtration Rate Estimating Equations in an Indian Population

Impact of the choice of biomarkers and equations to estimate kidney function on the epidemiology of chronic kidney disease

PURPOSE OF REVIEW

The CKD-EPI equations were updated in 2021 to remove the race variable from eGFR estimation. In the same year, the creatinine-based EKFC equation was published, subsequently supplemented by the cystatin C-based EKFC equation. Recent findings suggest that the prevalence of chronic kidney disease (CKD) can vary depending on the equation, the biomarker, and the population studied.

RECENT FINDINGS

Using the CKD-EPI2021 equation instead of the CKD-EPI2009 equation results in an increased prevalence of CKD among Black individuals in the U.S. and a decreased prevalence among non-Blacks. The CKD-EPI equations may underestimate the prevalence of CKD in India and in some sub-Saharan African populations. This is corrected by using the EKFC equation and dedicated Q-values. In general, the prevalence of CKD is slightly higher with EKFC than with the CKD-EPI equations. The CKD-EPIcys equation generally leads to a higher CKD prevalence than the CKD-EPIcrea equations. Few epidemiological data are available for EKFCcys.

SUMMARY

The choice of biomarkers and equations has an impact on the prevalence of CKD, with implications that also depend on the characteristics of the population being studied.