title: Development of an Australian cardiovascular disease mortality risk score using multiple imputation and recalibration from national statistics.
abstract: To develop and recalibrate an Australian 5-year cardiovascular disease (CVD) mortality risk score to produce contemporary predictions of risk.
  
  
  
  Data were pooled from six Australian cohort studies (n = 54,829), with baseline data collected between 1989 and 2003. Participants included were aged 40-74 years and free of CVD at baseline. Variables were harmonised across studies and missing data were imputed using multiple imputation. Cox proportional hazards models were used to estimate the risk of CVD mortality associated with factors mutually independently predictive (p < 0.05) and a 5-year risk prediction algorithm was constructed. This algorithm was recalibrated to reflect contemporary national levels of CVD mortality and risk factors using national statistics.
  
  
  
  Over a mean 16.6 years follow-up, 1375 participants in the six studies died from CVD. The prediction model included age, sex, smoking, diabetes, systolic blood pressure, total and high-density lipoprotein cholesterol (HDLC), a social deprivation score, estimated glomerular filtration rate and its square and interactions of sex with diabetes, HDLC and deprivation score, and of age with systolic blood pressure and smoking. This model discriminated well when applied to a Scottish study population (c-statistic (95% confidence interval): 0.751 (0.709, 0.793)). Recalibration generally increased estimated risks, but well below those predicted by the European SCORE models.
  
  
  
  The resulting risk score, which includes markers of both chronic kidney disease and socioeconomic deprivation, is the first CVD mortality risk prediction tool for Australia to be derived using Australian data. The primary model, and the method of recalibration, is applicable elsewhere.
authors.affiliation: Baker IDI Heart and Diabetes Institute, Melbourne, Australia. kathryn.backholer@deakin.edu.au.|Centre for Population Health, Deakin University, Melbourne, Australia. kathryn.backholer@deakin.edu.au.|School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia. kathryn.backholer@deakin.edu.au.
authors.forename: Kathryn
authors.initials: K
authors.lastname: Backholer
authors.affiliation: The George Institute for Global Health, University of Sydney, Sydney, Australia.
authors.forename: Yoichiro
authors.initials: Y
authors.lastname: Hirakawa
authors.affiliation: School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
authors.forename: Andrew
authors.initials: A
authors.lastname: Tonkin
authors.affiliation: Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia.
authors.forename: Graham
authors.initials: G
authors.lastname: Giles
authors.affiliation: Baker IDI Heart and Diabetes Institute, Melbourne, Australia.
authors.forename: Dianna J
authors.initials: DJ
authors.lastname: Magliano
authors.affiliation: The Boden Institute, University of Sydney, Sydney, Australia.
authors.forename: Stephen
authors.initials: S
authors.lastname: Colagiuri
authors.affiliation: The Centre for Primary Health Care and Equity, University of New South Wales, Sydney, Australia.
authors.forename: Mark
authors.initials: M
authors.lastname: Harris
authors.affiliation: Centre for Vision Research, Westmead Institute for Medical Research and University of Sydney, Westmead, Australia.
authors.forename: Paul
authors.initials: P
authors.lastname: Mitchell
authors.affiliation: Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia.
authors.forename: Mark
authors.initials: M
authors.lastname: Nelson
authors.affiliation: Baker IDI Heart and Diabetes Institute, Melbourne, Australia.
authors.forename: Jonathan E
authors.initials: JE
authors.lastname: Shaw
authors.affiliation: University of Melbourne, Melbourne, Australia.|Western Sydney University, Sydney, Australia.
authors.forename: David
authors.initials: D
authors.lastname: Simmons
authors.affiliation: UNSW Lipid Research Department, St Vincent's Hospital, Sydney, Australia.
authors.forename: Leon
authors.initials: L
authors.lastname: Simons
authors.affiliation: Population Research & Outcome Studies, The University of Adelaide, Adelaide, Australia.
authors.forename: Anne
authors.initials: A
authors.lastname: Taylor
authors.affiliation: Baker IDI Heart and Diabetes Institute, Melbourne, Australia.
authors.forename: Jessica
authors.initials: J
authors.lastname: Harding
authors.affiliation: Centre for Vision Research, Westmead Institute for Medical Research and University of Sydney, Westmead, Australia.
authors.forename: Bamini
authors.initials: B
authors.lastname: Gopinath
authors.affiliation: The George Institute for Global Health, University of Sydney, Sydney, Australia.|The George Institute for Global Health, University of Oxford, Oxford, UK.
authors.forename: Mark
authors.initials: M
authors.lastname: Woodward
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D002318:Cardiovascular Diseases / Q000401:mortality*; D005260:Female; D005500:Follow-Up Studies; D005544:Forecasting; D006305:Health Status Indicators; D006306:Health Surveys / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008875:Middle Aged; D009517:New South Wales / Q000453:epidemiology; D016016:Proportional Hazards Models; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D015996:Survival Rate / Q000639:trends
keywords: Cardiovascular disease; Imputation; Recalibration; Risk assessment