title: [Estimating glomerular filtration rate based on serum cystatin C].
abstract: OBJECTIVE
  To develop an estimating formula for glomerular filtration Rate (GFR) based on serum cystatin C in patients with chronic kidney disease (CKD).
  
  
  METHODS
  Clinical characteristics of 242 CKD patients were collected. The patients were randomly divided into modeling group and model validation group. The rGFR obtained from 99mTc-DTPA clearance rate was used as a reference value of GFR. s-cystatin C was detected by latex enhanced immunoturbidimetric method. Preliminary linear regression analysis followed by multiple linear regression were performed to investigate the association between s-cystatin C and rGFR. The validity of the estimation formula was tested in the model validation group in comparison with Hoek formula and Orebro formula.
  
  
  RESULTS
  With standardised countdown conversion, s-cystatin showed linear correlation with rGFR, with a correlation coefficient of 0.773. The multiple correlation coefficient, determination coefficient, adjusted R square and std. error of the estimation model were 0.863, 0.745, 0.742, and 0.207, respectively. The residuals P-P probability plot analysis showed that the model residuals fitted into normal distribution with homogeneity of variance. Theeformula was: eGFR = 67/s-cystatin C +3. No significant difference was found between the distribution of eGFR and rGFR. Our formula had an accuracy of 30% and 50%, which were no less than those obtained from Hoek formula and Orebro formula. The new formula also had acceptable bias and high precision. The Bland-Altman analysis and ROC curve analysis showed good applicability of the new formula.
  
  
  CONCLUSIONS
  The GFR prediction formula we established has a good prediction performance as comparised with other formulae, which could be used in measuring GFR in CKD patients.
authors.affiliation: Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, China.
authors.forename: Rui-Xue
authors.initials: RX
authors.lastname: Lü
authors.forename: Yi-Song
authors.initials: YS
authors.lastname: Li
authors.forename: Heng-Jian
authors.initials: HJ
authors.lastname: Huang
authors.forename: Zhi-Ying
authors.initials: ZY
authors.lastname: Peng
authors.forename: Bin-Wu
authors.initials: BW
authors.lastname: Ying
authors.forename: Zhen-Mei
authors.initials: ZM
authors.lastname: An
mesh_terms: D000328:Adult; D000368:Aged; D002908:Chronic Disease; D055316:Cystatin C / Q000097:blood*; D005260:Female; D005919:Glomerular Filtration Rate / Q000502:physiology*; D006801:Humans; D007674:Kidney Diseases / Q000378:metabolism / Q000503:physiopathology*; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D051436:Renal Insufficiency, Chronic / Q000378:metabolism / Q000503:physiopathology*; D015203:Reproducibility of Results
chemical_list: D055316:Cystatin C