title: The Framingham predictive instrument in chronic kidney disease.
abstract: OBJECTIVE
  We sought to determine the utility of the Framingham equations in individuals with chronic kidney disease (CKD).
  
  
  BACKGROUND
  The Framingham equations predict incident coronary disease. The utility of these equations is unknown in CKD.
  
  
  METHODS
  We pooled individuals without pre-existing coronary disease age 45 to 74 years from the ARIC (Atherosclerosis Risk In Communities) and CHS (Cardiovascular Health Study) trials with CKD, defined by an estimated glomerular filtration rate of 15 to 60 ml/min/1.73 m(2). Using gender-specific models, we determined 5- and 10-year risk of incident myocardial infarction and fatal coronary disease, and evaluated discriminative and calibration ability of the Framingham equations for predicting coronary events.
  
  
  RESULTS
  There were 577 women and 357 men with CKD. Thirty-five men (9.8%) and 30 women (5.2%) and 74 men (20.7%) and 56 women (9.7%) had cardiac events within 5 and 10 years, respectively; 5-year events were predicted in 6.0% and 1.9% and 10-year events in 13.9% and 4.8% of men and women, respectively. For 5-year events, C-statistics assessing discrimination were 0.62 and 0.77, while 10-year C-statistics were 0.60 and 0.73 for men and women, respectively. Calibration was also poor, with Framingham scores generally underpredicting events in individuals with CKD at 5 and 10 years. Discrimination was significantly improved by refitting models with population-specific coefficients, while recalibration improved prediction in women.
  
  
  CONCLUSIONS
  The Framingham instrument demonstrates poor overall accuracy in predicting cardiac events in individuals with CKD, although refit models can substantially improve discrimination. Calibration in women can be moderately improved with adjustment for higher event rates. Development of CKD-specific equations is needed.
authors.affiliation: Division of Nephrology, Tufts-New England Medical Center, Boston, Massachusetts 02111, USA. dweiner@tufts-nemc.org
authors.forename: Daniel E
authors.initials: DE
authors.lastname: Weiner
authors.forename: Hocine
authors.initials: H
authors.lastname: Tighiouart
authors.forename: Essam F
authors.initials: EF
authors.lastname: Elsayed
authors.forename: John L
authors.initials: JL
authors.lastname: Griffith
authors.forename: Deeb N
authors.initials: DN
authors.lastname: Salem
authors.forename: Andrew S
authors.initials: AS
authors.lastname: Levey
authors.forename: Mark J
authors.initials: MJ
authors.lastname: Sarnak
mesh_terms: D017677:Age Distribution; D000368:Aged; D016009:Chi-Square Distribution; D015331:Cohort Studies; D015897:Comorbidity; D003327:Coronary Disease / Q000175:diagnosis* / Q000453:epidemiology* / Q000628:therapy; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007676:Kidney Failure, Chronic / Q000175:diagnosis* / Q000453:epidemiology* / Q000628:therapy; D007677:Kidney Function Tests; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D015995:Prevalence; D011379:Prognosis; D006435:Renal Dialysis; D018570:Risk Assessment; D012720:Severity of Illness Index; D017678:Sex Distribution; D016019:Survival Analysis