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Development of an Australian cardiovascular disease mortality risk score using multiple imputation and recalibration from national statistics.
BMC Cardiovasc Disord. 2017 01 06; 17(1):17.BC

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.

Authors+Show Affiliations

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.The George Institute for Global Health, University of Sydney, Sydney, Australia.School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia.Baker IDI Heart and Diabetes Institute, 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.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.Baker IDI Heart and Diabetes Institute, Melbourne, Australia.University of Melbourne, Melbourne, Australia. Western Sydney University, Sydney, Australia.UNSW Lipid Research Department, St Vincent's Hospital, Sydney, Australia.Population Research & Outcome Studies, The University of Adelaide, Adelaide, Australia.Baker IDI Heart and Diabetes Institute, Melbourne, Australia.Centre for Vision Research, Westmead Institute for Medical Research and University of Sydney, Westmead, Australia.The George Institute for Global Health, University of Sydney, Sydney, Australia. The George Institute for Global Health, University of Oxford, Oxford, UK.

Pub Type(s)

Journal Article
Multicenter Study
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

28061760

Citation

Backholer, Kathryn, et al. "Development of an Australian Cardiovascular Disease Mortality Risk Score Using Multiple Imputation and Recalibration From National Statistics." BMC Cardiovascular Disorders, vol. 17, no. 1, 2017, p. 17.
Backholer K, Hirakawa Y, Tonkin A, et al. Development of an Australian cardiovascular disease mortality risk score using multiple imputation and recalibration from national statistics. BMC Cardiovasc Disord. 2017;17(1):17.
Backholer, K., Hirakawa, Y., Tonkin, A., Giles, G., Magliano, D. J., Colagiuri, S., Harris, M., Mitchell, P., Nelson, M., Shaw, J. E., Simmons, D., Simons, L., Taylor, A., Harding, J., Gopinath, B., & Woodward, M. (2017). Development of an Australian cardiovascular disease mortality risk score using multiple imputation and recalibration from national statistics. BMC Cardiovascular Disorders, 17(1), 17. https://doi.org/10.1186/s12872-016-0462-5
Backholer K, et al. Development of an Australian Cardiovascular Disease Mortality Risk Score Using Multiple Imputation and Recalibration From National Statistics. BMC Cardiovasc Disord. 2017 01 6;17(1):17. PubMed PMID: 28061760.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Development of an Australian cardiovascular disease mortality risk score using multiple imputation and recalibration from national statistics. AU - Backholer,Kathryn, AU - Hirakawa,Yoichiro, AU - Tonkin,Andrew, AU - Giles,Graham, AU - Magliano,Dianna J, AU - Colagiuri,Stephen, AU - Harris,Mark, AU - Mitchell,Paul, AU - Nelson,Mark, AU - Shaw,Jonathan E, AU - Simmons,David, AU - Simons,Leon, AU - Taylor,Anne, AU - Harding,Jessica, AU - Gopinath,Bamini, AU - Woodward,Mark, Y1 - 2017/01/06/ PY - 2016/09/13/received PY - 2016/12/23/accepted PY - 2017/1/8/entrez PY - 2017/1/8/pubmed PY - 2017/6/22/medline KW - Cardiovascular disease KW - Imputation KW - Recalibration KW - Risk assessment SP - 17 EP - 17 JF - BMC cardiovascular disorders JO - BMC Cardiovasc Disord VL - 17 IS - 1 N2 - 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. SN - 1471-2261 UR - https://www.unboundmedicine.com/medline/citation/28061760/Development_of_an_Australian_cardiovascular_disease_mortality_risk_score_using_multiple_imputation_and_recalibration_from_national_statistics_ L2 - https://bmccardiovascdisord.biomedcentral.com/articles/10.1186/s12872-016-0462-5 DB - PRIME DP - Unbound Medicine ER -