title: Comparison of risk prediction using the CKD-EPI equation and the MDRD study equation for estimated glomerular filtration rate.
abstract: BACKGROUND
  The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation more accurately estimates glomerular filtration rate (GFR) than the Modification of Diet in Renal Disease (MDRD) Study equation using the same variables, especially at higher GFR, but definitive evidence of its risk implications in diverse settings is lacking.
  
  
  OBJECTIVE
  To evaluate risk implications of estimated GFR using the CKD-EPI equation compared with the MDRD Study equation in populations with a broad range of demographic and clinical characteristics.
  
  
  METHODS
  A meta-analysis of data from 1.1 million adults (aged ≥ 18 years) from 25 general population cohorts, 7 high-risk cohorts (of vascular disease), and 13 CKD cohorts. Data transfer and analyses were conducted between March 2011 and March 2012.
  
  
  METHODS
  All-cause mortality (84,482 deaths from 40 cohorts), cardiovascular mortality (22,176 events from 28 cohorts), and end-stage renal disease (ESRD) (7644 events from 21 cohorts) during 9.4 million person-years of follow-up; the median of mean follow-up time across cohorts was 7.4 years (interquartile range, 4.2-10.5 years).
  
  
  RESULTS
  Estimated GFR was classified into 6 categories (≥90, 60-89, 45-59, 30-44, 15-29, and <15 mL/min/1.73 m(2)) by both equations. Compared with the MDRD Study equation, 24.4% and 0.6% of participants from general population cohorts were reclassified to a higher and lower estimated GFR category, respectively, by the CKD-EPI equation, and the prevalence of CKD stages 3 to 5 (estimated GFR <60 mL/min/1.73 m(2)) was reduced from 8.7% to 6.3%. In estimated GFR of 45 to 59 mL/min/1.73 m(2) by the MDRD Study equation, 34.7% of participants were reclassified to estimated GFR of 60 to 89 mL/min/1.73 m(2) by the CKD-EPI equation and had lower incidence rates (per 1000 person-years) for the outcomes of interest (9.9 vs 34.5 for all-cause mortality, 2.7 vs 13.0 for cardiovascular mortality, and 0.5 vs 0.8 for ESRD) compared with those not reclassified. The corresponding adjusted hazard ratios were 0.80 (95% CI, 0.74-0.86) for all-cause mortality, 0.73 (95% CI, 0.65-0.82) for cardiovascular mortality, and 0.49 (95% CI, 0.27-0.88) for ESRD. Similar findings were observed in other estimated GFR categories by the MDRD Study equation. Net reclassification improvement based on estimated GFR categories was significantly positive for all outcomes (range, 0.06-0.13; all P < .001). Net reclassification improvement was similarly positive in most subgroups defined by age (<65 years and ≥65 years), sex, race/ethnicity (white, Asian, and black), and presence or absence of diabetes and hypertension. The results in the high-risk and CKD cohorts were largely consistent with the general population cohorts.
  
  
  CONCLUSIONS
  The CKD-EPI equation classified fewer individuals as having CKD and more accurately categorized the risk for mortality and ESRD than did the MDRD Study equation across a broad range of populations.
authors.affiliation: Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.
authors.forename: Kunihiro
authors.initials: K
authors.lastname: Matsushita
authors.forename: Bakhtawar K
authors.initials: BK
authors.lastname: Mahmoodi
authors.forename: Mark
authors.initials: M
authors.lastname: Woodward
authors.forename: Jonathan R
authors.initials: JR
authors.lastname: Emberson
authors.forename: Tazeen H
authors.initials: TH
authors.lastname: Jafar
authors.forename: Sun Ha
authors.initials: SH
authors.lastname: Jee
authors.forename: Kevan R
authors.initials: KR
authors.lastname: Polkinghorne
authors.forename: Anoop
authors.initials: A
authors.lastname: Shankar
authors.forename: David H
authors.initials: DH
authors.lastname: Smith
authors.forename: Marcello
authors.initials: M
authors.lastname: Tonelli
authors.forename: David G
authors.initials: DG
authors.lastname: Warnock
authors.forename: Chi-Pang
authors.initials: CP
authors.lastname: Wen
authors.forename: Josef
authors.initials: J
authors.lastname: Coresh
authors.forename: Ron T
authors.initials: RT
authors.lastname: Gansevoort
authors.forename: Brenda R
authors.initials: BR
authors.lastname: Hemmelgarn
authors.forename: Andrew S
authors.initials: AS
authors.lastname: Levey
mesh_terms: D000368:Aged; D000465:Algorithms; D044466:Asian People / Q000706:statistics & numerical data; D044383:Black People / Q000706:statistics & numerical data; D002318:Cardiovascular Diseases / Q000401:mortality; D015331:Cohort Studies; D003661:Decision Support Techniques; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007676:Kidney Failure, Chronic / Q000401:mortality; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D018570:Risk Assessment / Q000379:methods*; D012737:Sex Factors; D044465:White People / Q000706:statistics & numerical data