Multimarker Prediction of Coronary Heart Disease Risk. The Women's Health Initiative

Hyeon Chang Kim; Philip Greenland; Jacques E. Rossouw; Jo Ann E. Manson; Barbara B. Cochrane; Norman L. Lasser; Marian C. Limacher; Donald M. Lloyd-Jones; Karen L. Margolis; Jennifer G. Robinson

doi:10.1016/j.jacc.2009.12.047

Multimarker Prediction of Coronary Heart Disease Risk. The Women's Health Initiative

Hyeon Chang Kim, Philip Greenland, Jacques E. Rossouw, Jo Ann E. Manson, Barbara B. Cochrane, Norman L. Lasser, Marian C. Limacher, Donald M. Lloyd-Jones, Karen L. Margolis, Jennifer G. Robinson

Department of Preventive Medicine and Public Health

Research output: Contribution to journal › Article › peer-review

95 Citations (Scopus)

Abstract

Objectives: The aim of this study was to investigate whether multiple biomarkers contribute to improved coronary heart disease (CHD) risk prediction in post-menopausal women compared with assessment using traditional risk factors (TRFs) only. Background: The utility of newer biomarkers remains uncertain when added to predictive models using only TRFs for CHD risk assessment. Methods: The Women's Health Initiative Hormone Trials enrolled 27,347 post-menopausal women ages 50 to 79 years. Associations of TRFs and 18 biomarkers were assessed in a nested case-control study including 321 patients with CHD and 743 controls. Four prediction equations for 5-year CHD risk were compared: 2 Framingham risk score covariate models; a TRF model including statin treatment, hormone treatment, and cardiovascular disease history as well as the Framingham risk score covariates; and an additional biomarker model that additionally included the 5 significantly associated markers of the 18 tested (interleukin-6, d-dimer, coagulation factor VIII, von Willebrand factor, and homocysteine). Results: The TRF model showed an improved C-statistic (0.729 vs. 0.699, p = 0.001) and net reclassification improvement (6.42%) compared with the Framingham risk score model. The additional biomarker model showed additional improvement in the C-statistic (0.751 vs. 0.729, p = 0.001) and net reclassification improvement (6.45%) compared with the TRF model. Predicted CHD risks on a continuous scale showed high agreement between the TRF and additional biomarker models (Spearman's coefficient = 0.918). Among the 18 biomarkers measured, C-reactive protein level did not significantly improve CHD prediction either alone or in combination with other biomarkers. Conclusions: Moderate improvement in CHD risk prediction was found when an 18-biomarker panel was added to predictive models using TRFs in post-menopausal women.

Original language	English
Pages (from-to)	2080-2091
Number of pages	12
Journal	Journal of the American College of Cardiology
Volume	55
Issue number	19
DOIs	https://doi.org/10.1016/j.jacc.2009.12.047
Publication status	Published - 2010 May 11

Bibliographical note

Funding Information:
The Women's Health Initiative is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts N01WH22110 , 24152 , 32100-2 , 32105-6 , 32108-9 , 32111-13 , 32115 , 32118-32119 , 32122 , 42107-26 , 42129-32 , and 44221 . The National Institutes of Health had input into the design and conduct of the study and in the review and approval of this article. Dr. Kim was partially supported by the Rose Stamler Fund for Young Investigators at Northwestern University. Dr. Robinson has received grants to institution from Abbott Laboratories, Aegerion Pharmaceuticals, AstraZeneca, Bristol-Myers Squibb, Daiichi Sankyo, GlaxoSmithKline, Hoffmann-La Roche, Merck, and Merck/Schering-Plough ; and is a consultant or advisory board member for AstraZeneca and Merck.

All Science Journal Classification (ASJC) codes

Cardiology and Cardiovascular Medicine

UN SDGs

This output contributes to the following Sustainable Development Goal(s)

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Kim, Hyeon Chang ; Greenland, Philip ; Rossouw, Jacques E. ; Manson, Jo Ann E. ; Cochrane, Barbara B. ; Lasser, Norman L. ; Limacher, Marian C. ; Lloyd-Jones, Donald M. ; Margolis, Karen L. ; Robinson, Jennifer G. / Multimarker Prediction of Coronary Heart Disease Risk. The Women's Health Initiative. In: Journal of the American College of Cardiology. 2010 ; Vol. 55, No. 19. pp. 2080-2091.

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title = "Multimarker Prediction of Coronary Heart Disease Risk. The Women's Health Initiative",

abstract = "Objectives: The aim of this study was to investigate whether multiple biomarkers contribute to improved coronary heart disease (CHD) risk prediction in post-menopausal women compared with assessment using traditional risk factors (TRFs) only. Background: The utility of newer biomarkers remains uncertain when added to predictive models using only TRFs for CHD risk assessment. Methods: The Women's Health Initiative Hormone Trials enrolled 27,347 post-menopausal women ages 50 to 79 years. Associations of TRFs and 18 biomarkers were assessed in a nested case-control study including 321 patients with CHD and 743 controls. Four prediction equations for 5-year CHD risk were compared: 2 Framingham risk score covariate models; a TRF model including statin treatment, hormone treatment, and cardiovascular disease history as well as the Framingham risk score covariates; and an additional biomarker model that additionally included the 5 significantly associated markers of the 18 tested (interleukin-6, d-dimer, coagulation factor VIII, von Willebrand factor, and homocysteine). Results: The TRF model showed an improved C-statistic (0.729 vs. 0.699, p = 0.001) and net reclassification improvement (6.42%) compared with the Framingham risk score model. The additional biomarker model showed additional improvement in the C-statistic (0.751 vs. 0.729, p = 0.001) and net reclassification improvement (6.45%) compared with the TRF model. Predicted CHD risks on a continuous scale showed high agreement between the TRF and additional biomarker models (Spearman's coefficient = 0.918). Among the 18 biomarkers measured, C-reactive protein level did not significantly improve CHD prediction either alone or in combination with other biomarkers. Conclusions: Moderate improvement in CHD risk prediction was found when an 18-biomarker panel was added to predictive models using TRFs in post-menopausal women.",

author = "Kim, {Hyeon Chang} and Philip Greenland and Rossouw, {Jacques E.} and Manson, {Jo Ann E.} and Cochrane, {Barbara B.} and Lasser, {Norman L.} and Limacher, {Marian C.} and Lloyd-Jones, {Donald M.} and Margolis, {Karen L.} and Robinson, {Jennifer G.}",

note = "Funding Information: The Women's Health Initiative is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts N01WH22110 , 24152 , 32100-2 , 32105-6 , 32108-9 , 32111-13 , 32115 , 32118-32119 , 32122 , 42107-26 , 42129-32 , and 44221 . The National Institutes of Health had input into the design and conduct of the study and in the review and approval of this article. Dr. Kim was partially supported by the Rose Stamler Fund for Young Investigators at Northwestern University. Dr. Robinson has received grants to institution from Abbott Laboratories, Aegerion Pharmaceuticals, AstraZeneca, Bristol-Myers Squibb, Daiichi Sankyo, GlaxoSmithKline, Hoffmann-La Roche, Merck, and Merck/Schering-Plough ; and is a consultant or advisory board member for AstraZeneca and Merck. ",

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doi = "10.1016/j.jacc.2009.12.047",

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Multimarker Prediction of Coronary Heart Disease Risk. The Women's Health Initiative. / Kim, Hyeon Chang; Greenland, Philip; Rossouw, Jacques E.; Manson, Jo Ann E.; Cochrane, Barbara B.; Lasser, Norman L.; Limacher, Marian C.; Lloyd-Jones, Donald M.; Margolis, Karen L.; Robinson, Jennifer G.

In: Journal of the American College of Cardiology, Vol. 55, No. 19, 11.05.2010, p. 2080-2091.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Multimarker Prediction of Coronary Heart Disease Risk. The Women's Health Initiative

AU - Kim, Hyeon Chang

AU - Greenland, Philip

AU - Rossouw, Jacques E.

AU - Manson, Jo Ann E.

AU - Cochrane, Barbara B.

AU - Lasser, Norman L.

AU - Limacher, Marian C.

AU - Lloyd-Jones, Donald M.

AU - Margolis, Karen L.

AU - Robinson, Jennifer G.

N1 - Funding Information: The Women's Health Initiative is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts N01WH22110 , 24152 , 32100-2 , 32105-6 , 32108-9 , 32111-13 , 32115 , 32118-32119 , 32122 , 42107-26 , 42129-32 , and 44221 . The National Institutes of Health had input into the design and conduct of the study and in the review and approval of this article. Dr. Kim was partially supported by the Rose Stamler Fund for Young Investigators at Northwestern University. Dr. Robinson has received grants to institution from Abbott Laboratories, Aegerion Pharmaceuticals, AstraZeneca, Bristol-Myers Squibb, Daiichi Sankyo, GlaxoSmithKline, Hoffmann-La Roche, Merck, and Merck/Schering-Plough ; and is a consultant or advisory board member for AstraZeneca and Merck.

PY - 2010/5/11

Y1 - 2010/5/11

N2 - Objectives: The aim of this study was to investigate whether multiple biomarkers contribute to improved coronary heart disease (CHD) risk prediction in post-menopausal women compared with assessment using traditional risk factors (TRFs) only. Background: The utility of newer biomarkers remains uncertain when added to predictive models using only TRFs for CHD risk assessment. Methods: The Women's Health Initiative Hormone Trials enrolled 27,347 post-menopausal women ages 50 to 79 years. Associations of TRFs and 18 biomarkers were assessed in a nested case-control study including 321 patients with CHD and 743 controls. Four prediction equations for 5-year CHD risk were compared: 2 Framingham risk score covariate models; a TRF model including statin treatment, hormone treatment, and cardiovascular disease history as well as the Framingham risk score covariates; and an additional biomarker model that additionally included the 5 significantly associated markers of the 18 tested (interleukin-6, d-dimer, coagulation factor VIII, von Willebrand factor, and homocysteine). Results: The TRF model showed an improved C-statistic (0.729 vs. 0.699, p = 0.001) and net reclassification improvement (6.42%) compared with the Framingham risk score model. The additional biomarker model showed additional improvement in the C-statistic (0.751 vs. 0.729, p = 0.001) and net reclassification improvement (6.45%) compared with the TRF model. Predicted CHD risks on a continuous scale showed high agreement between the TRF and additional biomarker models (Spearman's coefficient = 0.918). Among the 18 biomarkers measured, C-reactive protein level did not significantly improve CHD prediction either alone or in combination with other biomarkers. Conclusions: Moderate improvement in CHD risk prediction was found when an 18-biomarker panel was added to predictive models using TRFs in post-menopausal women.

AB - Objectives: The aim of this study was to investigate whether multiple biomarkers contribute to improved coronary heart disease (CHD) risk prediction in post-menopausal women compared with assessment using traditional risk factors (TRFs) only. Background: The utility of newer biomarkers remains uncertain when added to predictive models using only TRFs for CHD risk assessment. Methods: The Women's Health Initiative Hormone Trials enrolled 27,347 post-menopausal women ages 50 to 79 years. Associations of TRFs and 18 biomarkers were assessed in a nested case-control study including 321 patients with CHD and 743 controls. Four prediction equations for 5-year CHD risk were compared: 2 Framingham risk score covariate models; a TRF model including statin treatment, hormone treatment, and cardiovascular disease history as well as the Framingham risk score covariates; and an additional biomarker model that additionally included the 5 significantly associated markers of the 18 tested (interleukin-6, d-dimer, coagulation factor VIII, von Willebrand factor, and homocysteine). Results: The TRF model showed an improved C-statistic (0.729 vs. 0.699, p = 0.001) and net reclassification improvement (6.42%) compared with the Framingham risk score model. The additional biomarker model showed additional improvement in the C-statistic (0.751 vs. 0.729, p = 0.001) and net reclassification improvement (6.45%) compared with the TRF model. Predicted CHD risks on a continuous scale showed high agreement between the TRF and additional biomarker models (Spearman's coefficient = 0.918). Among the 18 biomarkers measured, C-reactive protein level did not significantly improve CHD prediction either alone or in combination with other biomarkers. Conclusions: Moderate improvement in CHD risk prediction was found when an 18-biomarker panel was added to predictive models using TRFs in post-menopausal women.

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Multimarker Prediction of Coronary Heart Disease Risk. The Women's Health Initiative

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

UN SDGs

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