title: The search for a new marker of renal function in older patients with chronic kidney disease stages 3-4: usefulness of cystatin C-based equations.
abstract: OBJECTIVE
  Cystatin C (Cys C) is an endogenous marker of glomerular filtration rate (GFR) unaffected by body composition. The aim of the present study was to assess the utility of Cys C-based GFR prediction equations (Hoek, Larsson and Stevens) and creatinine (modification of diet in renal disease-isotope dilution mass spectrometry--MDRD-IDMS, and Cockcroft-Gault--CG) compared with 51Cr-EDTA.
  
  
  METHODS
  This study was carried out in 40 Caucasian older patients with advanced age (> or = 60) and chronic kidney disease stages 3-4. To assess the utility of prediction equations in relation to body composition, we measured lean mass (LM) with densitometry (DXA). Pearson's, Bland-Altman and Lin's coefficient (Rc) were used to study accuracy and precision.
  
  
  RESULTS
  51Cr-EDTA was 36.9 +/- 9.2 ml/min/1.73 m2 (22-60). Cys C levels were 2.2 +/- 0.8 mg/l (r = 0.085; p = 0.662 LM) and creatinine 2.8 +/- 1.1 mg/dl (r = 0.427; p = 0.021 LM). The most accurate equations were the Hoek, Larsson and Stevens formulae, with a bias of -0.2 (Rc 0.48), -2.9 (Rc 0.44) and 2.6 ml/min/1.73 m2 (Rc 0.58). The biases obtained with MDRD-IDMS and CG were -14.6 (Rc 0.35) and -12.5 (Rc 0.40). All correlations among biases obtained with creatinine-based formulae and LM were negative and statistically significant (p < 0.05).
  
  
  CONCLUSIONS
  The results show superiority of Cys C-based GFR formulae over the MDRD-IDMS and CG equations. This significant underestimation obtained with conventional prediction equations was directly related to the influence of LM.
authors.affiliation: Department of Nephrology, Hospital Clínic de Barcelona, Barcelona, Spain. 34989nfb@comb.es
authors.forename: Néstor
authors.initials: N
authors.lastname: Fontseré
authors.forename: Vicens
authors.initials: V
authors.lastname: Esteve
authors.forename: Ana
authors.initials: A
authors.lastname: Saurina
authors.forename: Mónica
authors.initials: M
authors.lastname: Pou
authors.forename: Nuria
authors.initials: N
authors.lastname: Barba
authors.forename: Ramón
authors.initials: R
authors.lastname: Deulofeu
authors.forename: Silvana
authors.initials: S
authors.lastname: Di Gregorio
authors.forename: Luis Miguel
authors.initials: LM
authors.lastname: del Rio
authors.forename: Jose
authors.initials: J
authors.lastname: Rios
authors.forename: Ferran
authors.initials: F
authors.lastname: Torres
authors.forename: Franscesc
authors.initials: F
authors.lastname: Maduell
authors.forename: Josep M
authors.initials: JM
authors.lastname: Campistol
authors.forename: Manel
authors.initials: M
authors.lastname: Ramírez de Arellano
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D015415:Biomarkers / Q000652:urine; D055316:Cystatin C / Q000652:urine*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D007676:Kidney Failure, Chronic / Q000175:diagnosis* / Q000652:urine*; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D015415:Biomarkers; D055316:Cystatin C