title: Development and validation of a coronary risk prediction model for older U.S. and European persons in the Cardiovascular Health Study and the Rotterdam Study.
abstract: BACKGROUND
  Risk scores for prediction of coronary heart disease             (CHD) in older adults are needed.
  
  
  OBJECTIVE
  To develop a sex-specific CHD risk prediction model             for older adults that accounts for competing risks for death.
  
  
  METHODS
  2 observational cohort studies, using data from 4946             participants in the Cardiovascular Health Study (CHS) and 4303 participants in             the Rotterdam Study (RS).
  
  
  METHODS
  Community settings in the United States (CHS) and             Rotterdam, the Netherlands (RS).
  
  
  METHODS
  Persons aged 65 years or older who were free of             cardiovascular disease.
  
  
  METHODS
  A composite of nonfatal myocardial infarction and             coronary death.
  
  
  RESULTS
  During a median follow-up of 16.5 and 14.9 years,             1166 CHS and 698 RS participants had CHD events, respectively. Deaths from             noncoronary causes largely exceeded the number of CHD events, complicating             accurate CHD risk predictions. The prediction model had moderate ability to             discriminate between events and nonevents (c-statistic, 0.63 in both U.S. and             European men and 0.67 and 0.68 in U.S. and European women). The model was             well-calibrated; predicted risks were in good agreement with observed risks.             Compared with the Framingham point scores, the prediction model classified             elderly U.S. persons into higher risk categories but elderly European persons             into lower risk categories. Differences in classification accuracy were not             consistent and depended on cohort and sex. Adding newer cardiovascular risk             markers to the model did not substantially improve performance.
  
  
  CONCLUSIONS
  The model may be less applicable in nonwhite             populations, and the comparison Framingham model was not designed for adults             older than 79 years.
  
  
  CONCLUSIONS
  A CHD risk prediction model that accounts for deaths             from noncoronary causes among older adults provided well-calibrated risk             estimates but was not substantially more accurate than Framingham point scores.             Moreover, adding newer risk markers did not improve accuracy. These findings             emphasize the difficulties of predicting CHD risk in elderly persons and the             need to improve these predictions.
  
  
  BACKGROUND
  National Heart, Lung, and Blood Institute; National             Institute of Neurological Disorders and Stroke; The Netherlands Organisation             for Scientific Research; and the Netherlands Organisation for Health Research             and Development.
authors.affiliation: University Hospital Basel, Basel, Switzerland. mkoller@uhbs.ch
authors.forename: Michael T
authors.initials: MT
authors.lastname: Koller
authors.forename: Maarten J G
authors.initials: MJ
authors.lastname: Leening
authors.forename: Marcel
authors.initials: M
authors.lastname: Wolbers
authors.forename: Ewout W
authors.initials: EW
authors.lastname: Steyerberg
authors.forename: M G Myriam
authors.initials: MG
authors.lastname: Hunink
authors.forename: Rotraut
authors.initials: R
authors.lastname: Schoop
authors.forename: Albert
authors.initials: A
authors.lastname: Hofman
authors.forename: Heiner C
authors.initials: HC
authors.lastname: Bucher
authors.forename: Bruce M
authors.initials: BM
authors.lastname: Psaty
authors.forename: Donald M
authors.initials: DM
authors.lastname: Lloyd-Jones
authors.forename: Jacqueline C M
authors.initials: JC
authors.lastname: Witteman
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002423:Cause of Death; D003327:Coronary Disease / Q000453:epidemiology* / Q000401:mortality; D005260:Female; D006801:Humans; D015994:Incidence; D008297:Male; D015233:Models, Statistical; D015999:Multivariate Analysis; D009426:Netherlands / Q000453:epidemiology; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D014481:United States / Q000453:epidemiology; D044465:White People