#3503 impact of adopting the new ckd-epi 2021 equation on egfr and ckd detection in a multi-ethnic dutch population: the helius study

Abstract Background and Aims The 2009 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation is the current standard method for estimating GFR. There has been debate whether or not to exclude the race/ethnicity coefficient from this equation. Recently, the National Kidney Foundation and American Society of Nephrology Task Force on Reassessing Race in Diagnosing Kidney Disease recommended a new 2021 CKD-EPI race-free creatinine-based equation. The impact of this equation has not thoroughly been evaluated in the European population. We explored the impact of adopting this formula on both eGFR and estimates of CKD prevalence in a multi-ethnic Dutch population. Method We cross-sectionally analysed baseline data of 21,617 participants (mean age 44yr, 42% male) of the multi-ethnic HELIUS cohort study (Amsterdam, the Netherlands). Three groups were distinguished: participants of African Surinamese (4,151), Ghanaian (2,339) and other, non-African (15,127) background. eGFR was calculated using the 2009 and 2021 CKD-EPI equation. Multiple regression analyses were performed to determine differences in eGFR with additional adjustments for age, sex and traditional cardiovascular and renal risk factors. CKD prevalence (i.e., eGFR (<60mL/min/1.73m2) and/or ACR (≥3mg/mmol) was calculated. In each ethnic group three approaches to improve CKD case detection for both equations were compared by targeting participants with traditional renal risk factors (i.e., diabetes mellitus, hypertension or cardiovascular disease), by subsequently adding an age criterium (>40, >50, or >60 yrs), and low socio-economic status (none or elementary schooling). For each approach, c-statistics for CKD probability were compared. Results Differences between groups varied according to the equation used. Compared to participants with non-African backgrounds (mean eGFR 102 mL/min/1.73m2), age- and sex-adjusted differences (p<0.001) in the mean eGFR (SE) were 4.6±0.2 and -8.9±0.2 mL/min/1.73m2,in participants with African Surinamese, and 3.2±0.3 and -10.4±0.3 mL/min/1.73m2 in participants with Ghanaian background for the 2009 and 2021 CKD-EPI equations, respectively. Further adjustments did not change this. However, CKD prevalences were similar for both equations: 10.6% vs 10.8% (p = 0.30) in the whole cohort, 10.9 vs. 11.6% (p = 0.33) among African Surinamese and 12.0 vs 12.6% (p = 0.21) among Ghanaians. CKD case detection did not differ between the screening approaches nor between both equations. Also, c-statistics for CKD probabilities were not influenced by either equation. Conclusion In our cohort, adoption of the 2021 CKD-EPI equation leads to lower eGFR in participants of African Surinamese and Ghanaian background. However, only small not statistically significant differences in CKD prevalences, overall and in high-risk groups, were found. Our study indicates that discontinuation of the race-coefficient may have little impact on CKD detection in a multi-ethnic Dutch population.