title: Evaluation of the Chronic Kidney Disease Epidemiology Collaboration equation for estimating glomerular filtration rate in the Chinese population.
abstract: BACKGROUND
  Previous studies have indicated that the performance of glomerular filtration rate (GFR) estimation equations vary according to the races of the target population. The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation has not been validated in the Chinese population including patients with chronic kidney disease (CKD) and healthy controls.
  
  
  METHODS
  A total of 977 adult persons (682 patients with CKD and 295 healthy volunteers) from nine renal institutes of university hospitals located in nine geographic regions of China were enrolled in the study. A diagnostic test study comparing the CKD-EPI two-level and four-level race equation, the Modification of Diet in Renal Disease (MDRD) Study equation and the modified MDRD equation for Chinese (the Chinese equation). The (99m)Tc- diethylenetriamine pentaacetic acid dual plasma clearance was used as a reference method for measuring GFR.
  
  
  RESULTS
  The mean age of participants was 48.3 ± 16.0 years and 479 (49.0%) were male. The CKD-EPI two-level race equation and the Chinese equation performed better than the MDRD Study equation and CKD-EPI four-level race equation, with less bias (median difference between estimated GFR and reference GFR, 0.2 and 0.3 versus -2.4 and 3.0 mL/min/1.73 m(2)), improved precision (interquartile range of the difference, 20.5 and 20.8 versus 23.4 and 20.5 mL/min/1.73 m(2)) and greater accuracy (percentage of estimated GFR within 30% of reference GFR, 73.4 and 73.0% versus 69.8 and 70.1%).
  
  
  CONCLUSIONS
  The CKD-EPI two-level race equation and the Chinese equation performed similarly in the Chinese population, and both performed better than the MDRD Study equation and the CKD-EPI four-level race equation.
authors.affiliation: Department of Medicine, Peking University First Hospital, Beijing, China.
authors.forename: Xianglei
authors.initials: X
authors.lastname: Kong
authors.forename: Yingchun
authors.initials: Y
authors.lastname: Ma
authors.forename: Jianghua
authors.initials: J
authors.lastname: Chen
authors.forename: Qiong
authors.initials: Q
authors.lastname: Luo
authors.forename: Xueqing
authors.initials: X
authors.lastname: Yu
authors.forename: Ying
authors.initials: Y
authors.lastname: Li
authors.forename: Jinsheng
authors.initials: J
authors.lastname: Xu
authors.forename: Songmin
authors.initials: S
authors.lastname: Huang
authors.forename: Lining
authors.initials: L
authors.lastname: Wang
authors.forename: Wen
authors.initials: W
authors.lastname: Huang
authors.forename: Mei
authors.initials: M
authors.lastname: Wang
authors.forename: Guobin
authors.initials: G
authors.lastname: Xu
authors.forename: Luxia
authors.initials: L
authors.lastname: Zhang
authors.forename: Li
authors.initials: L
authors.lastname: Zuo
authors.forename: Haiyan
authors.initials: H
authors.lastname: Wang
mesh_terms: D000328:Adult; D016022:Case-Control Studies; D002681:China / Q000453:epidemiology; D003299:Cooperative Behavior; D003404:Creatinine / Q000097:blood; D005260:Female; D005500:Follow-Up Studies; D005919:Glomerular Filtration Rate; D006305:Health Status Indicators; D006801:Humans; D016030:Kidney Transplantation; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D051436:Renal Insufficiency, Chronic / Q000175:diagnosis* / Q000453:epidemiology* / Q000503:physiopathology; D012680:Sensitivity and Specificity
chemical_list: D003404:Creatinine