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Discordant Results Between Creatinine- and Cystatin C-based Equations for Estimating GFR
Pierre Delanaye1,2, Martin Flamant3, Emmanuelle Vidal-Petiot3
1Department of Nephrology-Dialysis-Transplantation, University of Liège, CHU Sart Tilman, Liège, Belgium.
Insights
Discordant glomerular filtration rate (GFR) estimates from cystatin C and creatinine are common. The European Kidney Function Consortium (EKFC) and reexpressed Lund-Malmö (r-LMR) equations are recommended over CKD-EPI for better accuracy in discordant cases.
Area of Science:
- Nephrology
- Clinical Chemistry
- Biomarker Research
Background:
- Discordance between cystatin C and creatinine in estimating glomerular filtration rate (GFR) presents a significant clinical challenge.
- The optimal equation for estimating GFR when these markers yield conflicting results remains unclear.
- Accurate GFR estimation is crucial for diagnosing and managing kidney disease.
Purpose of the Study:
- To evaluate the proportion of discordant GFR estimates using different equations (CKD-EPI, EKFC, r-LMR).
- To identify the most accurate GFR estimating equations for both concordant and discordant results.
- To provide guidance on selecting appropriate GFR estimation methods in clinical practice.
Main Methods:
- Cross-sectional analysis of 15,485 participants with measured GFR (mGFR).
- Comparison of GFR estimates from creatinine (eGFRcrea) and cystatin C (eGFRcys) using CKD-EPI, EKFC, and r-LMR equations.
- Definition of discordance based on absolute (>15 ml/min/1.73 m²) or relative (>20%) differences.
Main Results:
- The CKD-EPI equation showed a higher proportion of discordant results (35.1-40.6%) compared to EKFC (21.9-31.7%) and r-LMR (22.8-32.8%).
- For EKFC and r-LMR equations, the combined creatinine and cystatin C model most accurately estimated mGFR in discordant cases.
- CKD-EPI equations exhibited a higher tendency for eGFRcys < eGFRcrea, while EKFC and r-LMR showed a more balanced discrepancy.
Conclusions:
- The EKFC and r-LMR equations demonstrate lower GFR estimation discordance compared to CKD-EPI.
- These equations offer better concordance with measured GFR, particularly in cases of conflicting estimates.
- EKFC and r-LMR are recommended over CKD-EPI for more reliable GFR estimation, especially when results are discordant.
Introduction:
Discordant results between cystatin C and creatinine in estimating glomerular filtration rate (GFR) are an important medical issue. However, the equation that should be used when GFR estimates are discordant remains unclear.
Methods:
This cross-sectional analysis included 15,485 participants with GFR measured by the clearance of an exogenous marker, serum creatinine, and cystatin C. We studied the proportion of discordant results defined as an absolute (> 15 ml/min per 1.73 m2) or relative (> 20%) difference between creatinine-based estimated GFR (eGFR, eGFRcrea) and cystatin C-based eGFR (eGFRcys) using different equations (Chronic Kidney Disease Epidemiology Collaboration [CKD-EPI], European Kidney Function Consortium [EKFC], and reexpressed Lund-Malmö [r-LMR]). We also researched for the best estimating equations to be used in subjects with concordant or discordant results to estimate measured GFR (mGFR).
Results:
In the total cohort, the proportion of subjects with discordant results (absolute or relative) was larger for CKD-EPI (35.1 and 40.6%) than for EKFC (21.9 and 31.7%) or r-LMR (22.8 and 32.8%) equations. Among discrepant results, the proportion of eGFRcys < eGFRcrea was significantly higher than the proportion of eGFRcrea < eGFRcys for the CKD-EPI equations, whereas the occurrence of discrepancy was similar in the 2 discrepant groups for EKFC or r-LMR. For the EKFC and r-LMR equations, but not for the CKD-EPI, the equation combining creatinine and cystatin C was consistently the closest to the mGFR in the discrepant groups.
Conclusion:
Based on the lower discrepancy proportion, better balance between eGFRcrea and eGFRcys, and better concordance with mGFR, the EKFC, and r-LMR equations should be preferred over the CKD-EPI to estimate GFR.
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