Discussion
Accurate eGFR is important for detection and staging of CKD, drug dosing and decisions on administration of intravenous contrast. The recent KIDGO guidelines on CKD recommended using eGFRcr for the initial evaluation and then measuring cystatin C and using eGFRcys or eGFRcr-cys for confirmation in the clinical settings in which eGFRcr is less accurate. The difficulty in implementing this recommendation is that without the gold standard mGFR, physicians do not know when eGFRcr is inaccurate. Our analyses seek to provide clinicians with tools to know when to measure cystatin C based on the readily available clinical and demographic information and whether to report eGFRcys or eGFRcr-cys. Our results showed that eGFRcr and eGFRcys had similar accuracy in the total population, but differed across subgroups according to diabetes status and BMI at higher eGFRcr. However, eGFRcr-cys was as accurate or more accurate than eGFRcr and eGFRcys in most subgroups, including the subgroups in which eGFRcys was more accurate than eGFRcr. These results have important implications for future studies on endogenous filtration markers and use of GFR estimating equations in clinical practice.
GFR estimating equations use the serum level of the endogenous filtration markers, combined with demographic variables, such as age, sex and race, to account for unmeasured non-GFR determinants of the filtration markers that affect their serum levels (generation, tubular secretion or reabsorption, and extra-renal elimination). In principle, differences in bias between eGFRcr and eGFRcys may reflect differences in the non-GFR determinants of each marker that are not accounted for by the demographic variables in the estimating equations, and therefore, the improved accuracy of eGFRcr-cys over eGFRcr and eGFRcys reflects the smaller effects of the non-GFR determinants of each marker when they are used in combination. Neither BMI nor diabetes is included as a variable in the CKD-EPI estimating equations, so it is not unexpected that eGFRcr or eGFRcys may have differential bias across subgroups defined by these variables. Some of our findings can be accounted for by known non-GFR determinants in serum creatinine which are affected by these variables. The non-GFR determinants of serum cystatin C have not been carefully evaluated; more study will be required to determine how factors associated with the non-GFR determinants may affect our results.
Higher BMI is associated with higher muscle and fat mass. Muscle is the primary determinant of creatinine generation, and variation in muscle mass can affect serum creatinine concentration independently of GFR, leading to bias in eGFRcr compared with mGFR (overestimation at low BMI and underestimation at high BMI), as observed (Figure 1). Some studies suggest that fat mass may be a primary determinant of cystatin C generation, and if so, then variation in fat mass among individuals could affect serum cystatin C concentration independently of GFR, leading to bias in eGFRcys compared with mGFR. We observed differences in bias in both eGFRcr and eGFRcys across BMI groups (Figures 1 and 2), but a trend toward greater accuracy for eGFRcys than eGFRcr at low BMI and a lesser accuracy for eGFRcys than eGFRcr at higher BMI ( Table 3 ), which was significant at higher eGFRcr (Supplementary Table S1). However, this finding must be interpreted with caution because of the small number of people in these subgroups.
Diabetes is not known to be directly associated with the non-GFR determinants of serum creatinine. In this study, we observed small differences in the bias of eGFRcr between people according to the diabetes status, but not for eGFRcys (Figures 1 and 2 and Table 3 ). Prior studies by CKD-EPI and others have suggested some differences according to the diabetes status in the relationships of serum creatinine and cystatin C concentrations to mGFR, even after adjustment for age, sex and race, but efforts to incorporate diabetes as a variable in GFR estimating equations using either creatinine or cystatin C have not led to improved equation performance. Possibly, these differences reflect confounding by other variables. Possibly, differentiation of Type 1 from Type 2 diabetes may provide some insight.
These findings lead to specific suggestions for implementation of the KDIGO recommendations in practice. First, our findings indicate that eGFRcr-cys, but not eGFRcys, was more accurate than eGFRcr in most subgroups defined by age, sex, diabetes status, BMI or eGFRcr. They suggest that clinicians could measure cystatin C in most patients when more accurate eGFR is required, that clinical laboratories should report both eGFRcys and eGFRcr-cys when cystatin C is measured, and that clinicians should generally use eGFRcr-cys, rather than eGFRcys alone, for clinical decision making. Second, the findings suggest that cystatin C should be measured in patients with low BMI (<20 kg/m), especially if eGFRcr is high (>90 mL/min/1.73 m). eGFRcr may be substantially less accurate than eGFRcys in this subgroup and eGFRcys was as accurate as eGFRcr-cys. In clinical practice, this may be applicable to patients with low muscle mass (anorexia nervosa, malnutrition, neuromuscular disorders, limb amputation), although the accuracy of eGFRcys and eGFRcr-cys has not been established in these patients. eGFRcr may also be less accurate than eGFRcys in patients with diabetes, and eGFRcys was as accurate as eGFRcr-cys in this subgroup, but we are uncertain of the mechanism or the clinical relevance of these findings.
The findings of our study must be interpreted in light of its strengths and limitations. Strengths include the large study population, measurements of creatinine and cystatin C using standardized assays, and rigorous statistical analysis including point estimates and 95% CIs for subgroups defined by demographic and clinical characteristics and eGFRcr. However, there are also several limitations. We pooled studies of different populations which may have differed by characteristic or methods for measuring GFR, and we cannot rule out that some of the findings may reflect the characteristics of a particular study. In our previous work, we did not find that differences among studies affected our results. The study population did not include transplant recipients, a substantial number of blacks or patients with extremes of factors associated with non-GFR determinants of creatinine. We did not have data on a large number of variables and did not apply multivariable analysis to characterize factors that affect non-GFR determinants of creatinine versus cystatin C. We did not have data of albuminuria, a marker of kidney damage, but our prior work has not shown differences in equation performance by level of proteinuria. We could not differentiate Type 1 from Type 2 diabetes. Other studies with a more diverse study population and with data on more variables may be better suited for identification of likely factors most closely associated with non-GFR determinants of cystatin C. Indexing of mGFR and eGFR by BSA has been questioned in low- and high-BMI groups. In principle, differences between mGFR and eGFR may differ between indexed and non-indexed measures if the BSA is associated with non-GFR determinants of the endogenous filtration marker. Finally, measurement error in mGFR may contribute to imprecision in eGFR, but should have a smaller effect on differences between mGFR and eGFR based on different filtration markers.
In conclusion, we have demonstrated that eGFRcr-cys, but not eGFRcys, is more accurate than eGFRcr in most subgroups that we studied, suggesting preferential use of eGFRcr-cys when serum cystatin C is measured to obtain more accurate eGFR than can be obtained from eGFRcr alone. eGFRcys may be as accurate as eGFRcr-cys in patients with low BMI. Further studies are necessary to evaluate diagnostic strategies for using eGFRcys and eGFRcr-cys.