title: Which creatinine-based estimated glomerular filtration rate equation best predicts all-cause mortality in Chinese subjects with type 2 diabetes?
abstract: OBJECTIVE
  In Chinese, ethnicity-based and/or diabetes specific modifications of the Modification of Diet in Renal Disease (MDRD) and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations have been developed for determining estimated glomerular filtrate rate (eGFR). This study aimed to compare the performance of five different creatinine-based eGFR equations in predicting all-cause mortality among Chinese subjects with type 2 diabetes (T2DM).
  
  
  METHODS
  A total of 6739 Chinese subjects with T2DM were included. Their eGFR was calculated using the MDRD, CKD-EPI, their respective modified equations for Chinese, and the diabetes specific CKD-EPI Chinese T2DM equations. Multiple Cox regression analysis was used to evaluate the associations of eGFR with all-cause mortality. C-statistics, net reclassification index (NRI) and integrated discrimination index (IDI) were applied to assess the discrimination and reclassification of each eGFR equation in predicting mortality outcome.
  
  
  RESULTS
  Over a follow-up of 5.7years, the incidence of all-cause mortality was 12.9% (N=867). The CKD-EPI equation discriminated all-cause mortality better than the MDRD equation (C-statistics: 0.714 vs. 0.689, p<0.0001), and Chinese modification of their respective equations did not improve discrimination. Among the five eGFR equations evaluated, the CKD-EPI Chinese T2DM equation provided the best discrimination in predicting all-cause mortality among Chinese subjects with T2DM, and was the only equation providing a significantly positive NRI and IDI relative to the CKD-EPI equation.
  
  
  CONCLUSIONS
  Among Chinese subjects with T2DM, our findings suggested that the CKD-EPI Chinese T2DM equation best predicted all-cause mortality, and relative to the CKD-EPI equation, conferred improved discrimination and reclassification.
authors.affiliation: Department of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Research Centre of Heart, Brain, Hormone and Healthy Aging, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region.
authors.forename: C H
authors.initials: CH
authors.lastname: Lee
authors.affiliation: Department of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region.
authors.forename: A Z L
authors.initials: AZL
authors.lastname: Shih
authors.affiliation: Department of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region.
authors.forename: Y C
authors.initials: YC
authors.lastname: Woo
authors.affiliation: Department of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region.
authors.forename: C H Y
authors.initials: CHY
authors.lastname: Fong
authors.affiliation: Department of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region.
authors.forename: M M A
authors.initials: MMA
authors.lastname: Yuen
authors.affiliation: Department of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region. Electronic address: wschow01@gmail.com.
authors.forename: W S
authors.initials: WS
authors.lastname: Chow
authors.affiliation: Department of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region; Research Centre of Heart, Brain, Hormone and Healthy Aging, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region; State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region. Electronic address: ksllam@hku.hk.
authors.forename: K S L
authors.initials: KSL
authors.lastname: Lam
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002681:China / Q000453:epidemiology; D003404:Creatinine / Q000032:analysis* / Q000378:metabolism; D003924:Diabetes Mellitus, Type 2 / Q000150:complications* / Q000175:diagnosis / Q000401:mortality*; D005260:Female; D005500:Follow-Up Studies; D005919:Glomerular Filtration Rate; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011379:Prognosis; D012044:Regression Analysis; D051436:Renal Insufficiency, Chronic / Q000150:complications* / Q000175:diagnosis / Q000401:mortality*
chemical_list: D003404:Creatinine
keywords: Chinese; Mortality; Type 2 diabetes; eGFR equations