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


Backholer, K and Hirakawa, Y and Tonkin, A and Giles, G and Magliano, DJ and Colagiuri, S and Harris, M and Mitchell, P and Nelson, M and Shaw, JE and Simmons, D and Simons, L and Taylor, A and Harding, J and Gopinath, B and Woodward, M, Development of an Australian cardiovascular disease mortality risk score using multiple imputation and recalibration from national statistics, BMC Cardiovascular Disorders, 17, (1) Article 17. ISSN 1471-2261 (2017) [Refereed Article]


Copyright Statement

The Author(s) 2017. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)

DOI: doi:10.1186/s12872-016-0462-5


Objective: To develop and recalibrate an Australian 5-year cardiovascular disease (CVD) mortality risk score to produce contemporary predictions of risk.

Methods: Data were pooled from six Australian cohort studies (n=54,829), with baseline data collected between 1989 and 2003. Participants included were aged 4074 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.

Results: 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.

Conclusions: 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.

Item Details

Item Type:Refereed Article
Keywords:cardiovascular disease, risk assessment, imputation, recalibration
Research Division:Biomedical and Clinical Sciences
Research Group:Cardiovascular medicine and haematology
Research Field:Cardiology (incl. cardiovascular diseases)
Objective Division:Health
Objective Group:Clinical health
Objective Field:Clinical health not elsewhere classified
UTAS Author:Nelson, M (Professor Mark Nelson)
ID Code:115399
Year Published:2017
Web of Science® Times Cited:11
Deposited By:Menzies Institute for Medical Research
Deposited On:2017-03-22
Last Modified:2022-08-25
Downloads:92 View Download Statistics

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