Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/103674
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Type: Journal article
Title: Development of an Australian cardiovascular disease mortality risk score using multiple imputation and recalibration from national statistics
Author: Backholer, K.
Hirakawa, Y.
Tonkin, A.
Giles, G.
Magliano, D.
Colagiuri, S.
Harris, M.
Mitchell, P.
Nelson, M.
Shaw, J.
Simmons, D.
Simons, L.
Taylor, A.
Harding, J.
Gopinath, B.
Woodward, M.
Citation: BMC Cardiovascular Disorders, 2017; 17(1):17-1-17-9
Publisher: BioMed Central
Issue Date: 2017
ISSN: 1471-2261
1471-2261
Statement of
Responsibility: 
Kathryn Backholer, Yoichiro Hirakawa, Andrew Tonkin, Graham Giles, Dianna J. Magliano, Stephen Colagiuri, Mark Harris, Paul Mitchell, Mark Nelson, Jonathan E. Shaw, David Simmons, Leon Simons, Anne Taylor, Jessica Harding, Bamini Gopinath and Mark Woodward
Abstract: 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 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. 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.
Keywords: Cardiovascular disease; Imputation; Recalibration; Risk assessment
Rights: © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
RMID: 0030062373
DOI: 10.1186/s12872-016-0462-5
Grant ID: http://purl.org/au-research/grants/nhmrc/1002663
http://purl.org/au-research/grants/nhmrc/209057
http://purl.org/au-research/grants/nhmrc/251553
http://purl.org/au-research/grants/nhmrc/504711
Appears in Collections:Medical Sciences publications

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