We found that racial differences in prevalence estimates of CKD are very sensitive to the equation used to estimate GFR in a young, bi-racial cohort. When using the MDRD equation, whites had higher overall prevalence of CKD compared with blacks, due to a higher prevalence of stage 3 CKD among whites. In contrast, when using the CKD-EPI equation, not only was the overall prevalence of CKD reduced but we observed no race differences in CKD estimates. Moreover, when using the CARDIA-derived coefficient for the CKD-EPI equation, blacks had higher prevalence of CKD. Interestingly, despite having a higher prevalence of CKD stage 3 compared with blacks based on the validated equations, whites had a strikingly lower prevalence of risk factors for CKD. Rather than attributing this constellation of findings to an ‘epidemiological paradox’, we believe that an alternative explanation is that the current race coefficient for blacks may lead to a systematic misclassification of CKD among young blacks.
Our study shows that applying different race coefficients (1.21 in MDRD vs. 1.16 in CKD-EPI) in a young, healthy population significantly changes the association between race and CKD. This is of substantial importance epidemiologically as we attempt to understand why reports show that blacks have a lower prevalence of CKD [3
] but higher ESRD incidence compared with whites [1
]. Blacks have been shown to progress faster from CKD to ESRD [4
], but this faster progression may not fully account for the higher ESRD incidence rates.
Our findings also show that blacks who are classified as having CKD (eGFR <60 mL/min/1.73 m2) have much lower eGFR and a worse CKD risk factor profile compared with whites in CARDIA. The creatinine threshold required to reach an eGFR of 60 mL/min/1.73 m2 is substantially higher for blacks (1.7 mg/dL for a black man age 45 compared with 1.4 mg/dL for a white man age 45). In young adults, it is unclear whether these creatinine differences are solely a correction for muscle mass or rather represent different severities of kidney disease.
Most interestingly, despite a much lower prevalence of risk factors for CKD, whites had a higher prevalence of CKD stage 3. If the current classification is accurate, then we would expect whites near the CKD cut-off to have higher severity of risk factors for CKD. However, we found that among those with eGFR 60–80 mL/min/1.73 m2
, blacks had much higher prevalence of CKD-associated abnormalities and risk factors, particularly albuminuria, a critical marker of kidney damage. Although our study cannot determine the exact coefficient appropriate for young blacks, it is likely that the current most clinically available 21% higher eGFR for the same serum creatinine (i.e. MDRD equation) may misclassify young blacks as having no CKD. In addition, since the prevalence of CKD varied even further among whites than blacks using MDRD vs. CKD-EPI equations, it is possible that whites may be mislabelled as having CKD. These equations have not been validated in young adults with no established CKD. Importantly, the prevalence of stages 4 and 5 did not vary among blacks using either MDRD or CKD-EPI equation, where equations were developed and thus are thought to be most accurate [5,11
]. These findings are of major importance because the current use of race coefficients in estimating equations may systematically misclassify young blacks as low CKD risk, and only capture them at advanced stages of disease, or mislabel whites as having CKD. Unfortunately, until a population-based study measures GFR in healthy, young adults, we cannot discern the extent of misclassification in whites and blacks.
Our study is the first to explore the impact of the current creatinine-based equations on CKD prevalence estimates by race and gender. We used a large, well-characterized young cohort with calibrated serum creatinine measures. We used both the accepted standard and the newly improved estimating equations for these analyses in addition to a CARDIA-derived coefficient. However, our study is limited by its cross-sectional nature, so it cannot assess the progression of CKD. We may also be limited by the overall low prevalence of CKD in this cohort. In addition, we did not have gold standard GFR measures to establish true CKD status. Unfortunately, no community-based study of blacks without CKD has measured GFR to date. Although we show that blacks near the CKD threshold have higher albuminuria and higher serum uric acid levels, we do not have information on other important metabolic parameters associated with CKD.
In summary, we found that CKD classification among blacks is very sensitive to the race coefficients of the current GFR-estimating equations, particularly at stage 3. Although whites had a higher prevalence of CKD stage 3 compared with blacks, their CKD risk factor profile was strikingly better than that of blacks. Our findings suggest that the current equations may underestimate CKD in blacks, particularly at stage 3, where interventions are most crucial. Future studies to develop GFR-estimating equations should include young, healthy, non-white populations and should consider alternative filtration markers that may be less biased by race.