title: Different equations to combine creatinine and cystatin C to predict GFR. Arithmetic mean of existing equations performs as well as complex combinations.
abstract: OBJECTIVE
  To test various ways of combining creatinine and cystatin C in equations to predict glomerular filtration rate (GFR).
  
  
  METHODS
  Performance of the following expressions to predict GFR was compared with measured GFR (iohexol clearance, mL/min/1.73 m(2)) in 857 patients: (i) Lund-Malmö creatinine equation, (ii) Grubb cystatin C equation, (iii) arithmetic mean of (1) and (2), (iv) geometric mean of (1) and (2), (v) linear regression on (1) and (2), (vi) regression on (1) and cystatin C, and (vii) regression on creatinine, cystatin C, age and gender.
  
  
  RESULTS
  For the entire cohort median percent error (bias) was <5% for all expressions, though all expressions tended to underestimate (-8.3 to 15.8%) GFR at levels > or =90 mL/min/1.73 m(2). The five expressions combining creatinine and cystatin C significantly improved correlation and accuracy (p<0.001) within 15 and 30% of measured GFR compared with the equations based on the separate analytes and with no significant difference between the five expressions. In a subgroup of patients with neurological disease and muscle atrophy the cystatin C equation performed better than the expressions combining creatinine and cystatin C.
  
  
  CONCLUSIONS
  Simply calculating the arithmetic mean of predicted GFR based on separate creatinine and cystatin C equations performs equally well as more complex equations. Reporting GFR based on separate creatinine and cystatin C equations, and their arithmetic mean also has the definite advantage that the physician can choose the estimated GFR, most appropriate depending on the clinical setting and patient characteristics.
authors.affiliation: Department of Radiology, Lasarettet Trelleborg, Trelleborg, Sweden. ulf.nyman@skane.se
authors.forename: Ulf
authors.initials: U
authors.lastname: Nyman
authors.forename: Anders
authors.initials: A
authors.lastname: Grubb
authors.forename: Gunnar
authors.initials: G
authors.lastname: Sterner
authors.forename: Jonas
authors.initials: J
authors.lastname: Björk
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000886:Anthropometry; D015982:Bias; D015331:Cohort Studies; D003404:Creatinine / Q000097:blood*; D055316:Cystatin C / Q000097:blood*; D003710:Demography; D005260:Female; D005919:Glomerular Filtration Rate / Q000502:physiology*; D006801:Humans; D007472:Iohexol / Q000378:metabolism; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D012372:ROC Curve
chemical_list: D055316:Cystatin C; D007472:Iohexol; D003404:Creatinine