Why the study?
Which estimated GFR equation best identifies moderate chronic kidney disease compared to inulin clearance in stable CKD patients?
Which estimated GFR equation best identifies moderate chronic kidney disease compared to inulin clearance in stable CKD patients?
Current eGFR equations lack consistent good performance to define moderate CKD, suggesting a combination of sensitive and specific equations may be needed for epidemiological studies.
No single eGFR equation optimally balances sensitivity and specificity for moderate CKD; leaves open whether combinations improve epidemiological accuracy.
BACKGROUND: The objective of this study was to identify which formula may best identify moderate chronic kidney disease (CKD) (glomerular filtration rate (GFR) cut-off of 60 ml/min/1.73 m(2)). METHODS: We compared the performances of 14 serum creatinine (S(cr)) and 11 cystatin C (Cys C) estimated GFR equations using inulin clearance (Cl(in)) as the reference test in a stable CKD population of 101 patients. Scatter, coefficient of variation, bias, precision, accuracy within 30% ranges from the reference method, agreements and receiving operating characteristics (ROC) of each test were compared. RESULTS: ROC analysis identified Davis, Salzar, Virga and Cockcroft-Gault as the most sensitive (>or=85%) and the isotope dilution mass spectrometry (IDMS), Edwards, MacIsaac as the most specific (95%) to define the GFR cut-off level of 60 ml/min/1.73 m(2). Area under the ROC curve (AUC) was generally >0.8 (p <or= 0.0001). 2 x 2 contingency tables to define CKD demonstrated sensitivity of 90% for Davis, while the IDMS was the most specific (95%). Among the Cys-C-based equations, Filler was the most sensitive (83%) and MacIsaac was the most specific (95%). CONCLUSION: The current equations lack consistent good performance to define CKD. The MDRD-IDMS equation missed 30% but demonstrated a high specificity to confirm those with moderate CKD. A combination of two equations, one sensitive and another specific, may be required for epidemiological studies.
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Emara et al. (2008) studied this question.
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