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

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 A Simons, Anne Taylor, Jessica Harding, Bamini Gopinath, Mark Woodward

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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 16.6years 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.

Original languageEnglish
Article number17
JournalBMC Cardiovascular Disorders
Volume17
Issue number17
DOIs
Publication statusPublished - 6 Jan 2017

Keywords

  • Cardiovascular disease
  • Imputation
  • Recalibration
  • Risk assessment

Cite this

Backholer, Kathryn ; Hirakawa, Yoichiro ; Tonkin, Andrew ; Giles, Graham ; Magliano, Dianna J. ; Colagiuri, Stephen ; Harris, Mark ; Mitchell, Paul ; Nelson, Mark ; Shaw, Jonathan E. ; Simmons, David ; Simons, Leon A ; Taylor, Anne ; Harding, Jessica ; Gopinath, Bamini ; Woodward, Mark. / Development of an Australian cardiovascular disease mortality risk score using multiple imputation and recalibration from national statistics. In: BMC Cardiovascular Disorders. 2017 ; Vol. 17, No. 17.
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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 16.6years 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.",
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author = "Kathryn Backholer and Yoichiro Hirakawa and Andrew Tonkin and Graham Giles and Magliano, {Dianna J.} and Stephen Colagiuri and Mark Harris and Paul Mitchell and Mark Nelson and Shaw, {Jonathan E.} and David Simmons and Simons, {Leon A} and Anne Taylor and Jessica Harding and Bamini Gopinath and Mark Woodward",
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Development of an Australian cardiovascular disease mortality risk score using multiple imputation and recalibration from national statistics. / Backholer, Kathryn; Hirakawa, Yoichiro; Tonkin, Andrew; Giles, Graham; Magliano, Dianna J.; Colagiuri, Stephen; Harris, Mark; Mitchell, Paul; Nelson, Mark; Shaw, Jonathan E.; Simmons, David; Simons, Leon A; Taylor, Anne; Harding, Jessica; Gopinath, Bamini; Woodward, Mark.

In: BMC Cardiovascular Disorders, Vol. 17, No. 17, 17, 06.01.2017.

Research output: Contribution to journalArticleResearchpeer-review

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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 A

AU - Taylor, Anne

AU - Harding, Jessica

AU - Gopinath, Bamini

AU - Woodward, Mark

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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 16.6years 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.

AB - 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 16.6years 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.

KW - Cardiovascular disease

KW - Imputation

KW - Recalibration

KW - Risk assessment

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U2 - 10.1186/s12872-016-0462-5

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JO - BMC Cardiovascular Disorders

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SN - 1471-2261

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