title: Distribution of reference GFR in a development population: a critical factor for the establishment of a GFR estimation equation.
abstract: OBJECTIVE
  Our previous work showed that the performance of MDRD equations could be improved by modifying the original MDRD equation. However, during the modification we recognized that reference GFR (rGFR) distribution was not similar between the MDRD study and the Chinese Estimating GFR (eGFR) Investigation Study. This present study was designed to illustrate that the GFR estimating equation might be influenced by the difference of rGFR distribution in the development population. Racial factors might not be as important as once thought.
  
  
  METHODS
  The Chinese eGFR Investigation Study dataset containing 684 CKD patients was defined as Dataset I, the modified MDRD equation for Chinese was defined as Equation 1. Datasets II and III were generated respectively by deleting 125 cases of CKD Stage 1 from Dataset I and by adding 297 cases of apparently healthy Chinese adults into Dataset I. eGFR was estimated using Equation 1. Using rGFR as dependent and eGFR as independent, linear regression models were constructed using Dataset II and Dataset III, respectively, and generated Equation 2 and Equation 3. The prevalence of eGFR less than 60 ml/min/1.73 m2 in the adult Beijing population was calculated using Equation 1, 2 and 3.
  
  
  RESULTS
  The previous reported prevalence of decreased GFR using Equation 1 in the Beijing adult population was 1.3% (0.8 - 1.8). By using Equation 2 and Equation 3, the prevalence increased to 3.2% (2.49 - 4.13) and decreased to 0.8% (0.57 - 1.28), respectively.
  
  
  CONCLUSIONS
  GFR estimating equation was influenced by rGFR distribution of the development dataset.
authors.affiliation: Department of Nephrology, China Rehabilitation Research Center, BeiJing BoAi Hospital, Capital Medical University Rehabilitation Medical College.
authors.forename: Y-C
authors.initials: YC
authors.lastname: Ma
authors.forename: L
authors.initials: L
authors.lastname: Zuo
authors.forename: Z-M
authors.initials: ZM
authors.lastname: Su
authors.forename: L
authors.initials: L
authors.lastname: Chen
authors.forename: S
authors.initials: S
authors.lastname: Meng
authors.forename: J-J
authors.initials: JJ
authors.lastname: Li
authors.forename: C-L
authors.initials: CL
authors.lastname: Zhang
authors.forename: H-Y
authors.initials: HY
authors.lastname: Wang
mesh_terms: D015415:Biomarkers / Q000097:blood; D002681:China; D003404:Creatinine / Q000097:blood; D003710:Demography; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007676:Kidney Failure, Chronic / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D012016:Reference Values
chemical_list: D015415:Biomarkers; D003404:Creatinine