Development of an Australian cardiovascular disease mortality risk score using multiple imputation and recalibration from national statistics

BMC Cardiovascular Disorders

Research Article

Jonathan E. Shaw¹  Dianna J. Magliano¹  Jessica Harding¹  Kathryn Backholer²  Graham Giles³  Paul Mitchell⁴  Bamini Gopinath⁴  Mark Nelson⁵  Anne Taylor⁶  Andrew Tonkin⁷  Stephen Colagiuri⁸  Mark Harris⁹  Yoichiro Hirakawa^1,10  Mark Woodward^1,11  Leon Simons^1,12  David Simmons^1,13 

[1] Baker IDI Heart and Diabetes Institute, Melbourne, Australia;Baker IDI Heart and Diabetes Institute, Melbourne, Australia;Centre for Population Health, Deakin University, Melbourne, Australia;School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia;Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia;Centre for Vision Research, Westmead Institute for Medical Research and University of Sydney, Westmead, Australia;Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia;Population Research & Outcome Studies, The University of Adelaide, Adelaide, Australia;School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia;The Boden Institute, University of Sydney, Sydney, Australia;The Centre for Primary Health Care and Equity, University of New South Wales, Sydney, Australia;The George Institute for Global Health, University of Sydney, Sydney, Australia;The George Institute for Global Health, University of Sydney, Sydney, Australia;The George Institute for Global Health, University of Oxford, Oxford, UK;UNSW Lipid Research Department, St Vincent’s Hospital, Sydney, Australia;University of Melbourne, Melbourne, Australia;Western Sydney University, Sydney, Australia;

关键词: Cardiovascular disease;    Risk assessment;    Imputation;    Recalibration;   

DOI  :  10.1186/s12872-016-0462-5

 received in 2016-09-13, accepted in 2016-12-23,  发布年份 2017

来源: Springer

【 摘 要 】

ObjectiveTo develop and recalibrate an Australian 5-year cardiovascular disease (CVD) mortality risk score to produce contemporary predictions of risk.MethodsData 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.ResultsOver 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.ConclusionsThe 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.

【 授权许可】

CC BY   
© The Author(s). 2017

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