title: Estimating glomerular filtration rate: comparison of the CKD-EPI and MDRD equations in a large UK cohort with particular emphasis on the effect of age.
abstract: BACKGROUND
  The chronic kidney disease (CKD)-Epidemiology Collaboration (CKD-EPI) equation was developed to address the underestimation of measured glomerular filtration rate (GFR) by the Modification of Diet in Renal Disease (MDRD) equation at levels >60 mL/min/1.73 m(2).
  
  
  OBJECTIVE
  To assess the impact of the CKD-EPI equation on the estimation of GFR in a large adult UK population (n = 561,400), particularly looking at the effect of age.
  
  
  METHODS
  Serum creatinine results (ID-MS-aligned enzymatic assay) were extracted from the pathology database during 1 year on adult (≥ 18 years) patients from primary care.
  
  
  METHODS
  The first available creatinine result from 174,448 people was used to estimate GFR using both equations and agreement assessed.
  
  
  RESULTS
  Median CKD-EPI GFR was significantly higher than median MDRD GFR (82 vs. 76 mL/min/1.73 m(2), P < 0.0001). Overall mean bias between CKD-EPI and MDRD GFR was 5.0%, ranging from 13.0% in the 18-29 years age group down to -7.5% in those aged ≥ 90 years. Although statistically significant at all age groups the difference diminished with age and the agreement in GFR category assignment increased. Age-adjusted population prevalence of CKD Stages 3-5 was lower by CKD-EPI than by MDRD (4.4% vs. 4.9%).
  
  
  CONCLUSIONS
  CKD-EPI produces higher GFR and lower CKD estimates, particularly among 18-59 year age groups with MDRD estimated GFRs of 45-59 mL/min/1.73 m(2) (Stage 3A). However, at ages >70 years there is very little difference between the equations, and among the very elderly CKD-EPI may actually increase CKD prevalence estimates.
authors.affiliation: Clinical Biochemistry, East Kent Hospitals University NHS Foundation Trust, Kent and Canterbury Hospital, Ethelbert Road, Canterbury, Kent CT1 3NG, UK. joanne.carter@ekht.nhs.uk
authors.forename: J L
authors.initials: JL
authors.lastname: Carter
authors.forename: P E
authors.initials: PE
authors.lastname: Stevens
authors.forename: J E
authors.initials: JE
authors.lastname: Irving
authors.forename: E J
authors.initials: EJ
authors.lastname: Lamb
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000097:blood / Q000502:physiology*; D000465:Algorithms; D015415:Biomarkers / Q000097:blood; D015331:Cohort Studies; D003404:Creatinine / Q000097:blood; D004739:England / Q000453:epidemiology; D005260:Female; D005919:Glomerular Filtration Rate / Q000502:physiology*; D006801:Humans; D007676:Kidney Failure, Chronic / Q000175:diagnosis* / Q000453:epidemiology / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D055815:Young Adult
chemical_list: D015415:Biomarkers; D003404:Creatinine