title: Glomerular filtration rate estimation in patients with type 2 diabetes: creatinine- or cystatin C-based equations?
abstract: OBJECTIVE
  It is argued that GFR estimation (eGFR) using cystatin C-based equations (eGFRcys) is superior to that using creatinine-based equations (eGFRcre). We investigated whether eGFRcys are superior to eGFRcre in patients with type 2 diabetes.
  
  
  METHODS
  GFR was measured in 448 type 2 diabetic patients using (51)Cr-EDTA-measured GFR (mGFR) as the reference standard. Bias, precision and accuracy of eGFRcys and eGFRcre were compared.
  
  
  RESULTS
  The most accurate eGFRcre equation (Chronic Kidney Disease Epidemiology Collaboration [CKD-EPI]), which produced the highest proportion of estimates that were within 30% and 10% of the reference standard (80.7% and 38.0% of samples, respectively) had a bias of 7.1 and precision of 12.0 ml min(-1) 1.73 m(-2). The calibrated eGFRcys with the highest accuracy (Tan-C), which produced the highest proportion of estimates that were within 30% (78.8%) and within 10% (39.0%) of the reference standard had a bias of -3.5 and precision of 18.0 ml min(-1) 1.73 m(-2). Moreover, the areas under the receiver operating curve were higher with eGFRcre (CKD-EPI and Modification of Diet in Renal Disease [MDRD]) than with eGFRcys for the diagnosis of mild (mGFR <90 ml min(-1) 1.73 m(-2)) and moderate (mGFR <60 ml min(-1) 1.73 m(-2)) chronic kidney disease. In patients with mGFR ≥90 ml min(-1) 1.73 m(-2), CKD-EPI was the least biased, the most precise and the most accurate equation.
  
  
  CONCLUSIONS
  In patients with type 2 diabetes, eGFRcys do not currently provide better eGFR than eGFRcre. At present, compared with eGFRcys, eGFRcre are better at predicting the stage of chronic kidney disease. In addition, CKD-EPI seems to be the best equation for eGFR in patients with normal renal function.
authors.affiliation: First Propedeutic Department of Internal Medicine, University General Hospital AHEPA, S. Kyriakidi Street 1, 54636 Thessaloniki, Greece. iliadis@med.auth.gr
authors.forename: F
authors.initials: F
authors.lastname: Iliadis
authors.forename: T
authors.initials: T
authors.lastname: Didangelos
authors.forename: A
authors.initials: A
authors.lastname: Ntemka
authors.forename: A
authors.initials: A
authors.lastname: Makedou
authors.forename: E
authors.initials: E
authors.lastname: Moralidis
authors.forename: A
authors.initials: A
authors.lastname: Gotzamani-Psarakou
authors.forename: T
authors.initials: T
authors.lastname: Kouloukourgiotou
authors.forename: D
authors.initials: D
authors.lastname: Grekas
mesh_terms: D000368:Aged; D003404:Creatinine / Q000097:blood*; D003430:Cross-Sectional Studies; D055316:Cystatin C / Q000097:blood*; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000503:physiopathology*; D003928:Diabetic Nephropathies / Q000097:blood* / Q000175:diagnosis; D005260:Female; D005919:Glomerular Filtration Rate / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D012372:ROC Curve; D051436:Renal Insufficiency, Chronic / Q000175:diagnosis / Q000503:physiopathology; D015203:Reproducibility of Results
chemical_list: D055316:Cystatin C; D003404:Creatinine