Glycated hemoglobin measurement and prediction of cardiovascular disease

Emanuele Di Angelantonio, Pei Gao, Hassan Khan, Adam S. Butterworth, David Wormser, Stephen Kaptoge, Sreenivasa Rao Kondapally Seshasai, Alex Thompson, Nadeem Sarwar, Peter Willeit, Paul M. Ridker, Elizabeth L.M. Barr, Kay Tee Khaw, Bruce M. Psaty, Hermann Brenner, Beverley Balkau, Jacqueline M. Dekker, Debbie A. Lawlor, Makoto Daimon, Johann Willeit & 56 others Inger Njølstad, Aulikki Nissinen, Eric J. Brunner, Lewis H. Kuller, Jackie F. Price, Johan Sundström, Matthew W. Knuiman, Edith J.M. Feskens, W. M.M. Verschuren, Nicholas Wald, Stephan J.L. Bakker, Peter H. Whincup, Ian Ford, Uri Goldbourt, Agustín Gómez-de-la-Cámara, John Gallacher, Leon A. Simons, Annika Rosengren, Susan E. Sutherland, Cecilia Björkelund, Dan G. Blazer, Sylvia Wassertheil-Smoller, Altan Onat, Alejandro Marín Ibañez, Edoardo Casiglia, J. Wouter Jukema, Lara M. Simpson, Simona Giampaoli, Børge G. Nordestgaard, Randi Selmer, Patrik Wennberg, Jussi Kauhanen, Jukka T. Salonen, Rachel Dankner, Elizabeth Barrett-Connor, Maryam Kavousi, Vilmundur Gudnason, Denis Evans, Robert B. Wallace, Mary Cushman, Ralph B. D'Agostino, Jason G. Umans, Yutaka Kiyohara, Hidaeki Nakagawa, Shinichi Sato, Richard F. Gillum, Aaron R. Folsom, Yvonne T. van der Schouw, Karel G. Moons, Simon J. Griffin, Naveed Sattar, Nicholas J. Wareham, Elizabeth Selvin, Simon G. Thompson, John Danesh, The Emerging Risk Factors Collaboration

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Importance: The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain.

Objective: To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk.

Design, Setting, and Participants: Analysis of individual-participant data available from 73 prospective studies involving 294 998 participants without a known history of diabetes mellitus or CVD at the baseline assessment.

Main Outcomes and Measures: Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5% to <7.5%), and high (≥7.5%) risk.

Results: During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20 840 incident fatal and nonfatal CVD outcomes (13 237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (−0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels.

Conclusions and Relevance: 
In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk.

Original languageEnglish
Pages (from-to)1225-1233
Number of pages9
JournalJAMA - Journal of the American Medical Association
Volume311
Issue number12
DOIs
Publication statusPublished - 26 Mar 2014
Externally publishedYes

Fingerprint

Glycosylated Hemoglobin A
Cardiovascular Diseases
Glomerular Filtration Rate
C-Reactive Protein
HDL Cholesterol
Coronary Disease
Fasting
Diabetes Mellitus
Triglycerides
Stroke
Cholesterol
Outcome Assessment (Health Care)
Prospective Studies

Cite this

Di Angelantonio, E., Gao, P., Khan, H., Butterworth, A. S., Wormser, D., Kaptoge, S., ... The Emerging Risk Factors Collaboration (2014). Glycated hemoglobin measurement and prediction of cardiovascular disease. JAMA - Journal of the American Medical Association, 311(12), 1225-1233. https://doi.org/10.1001/jama.2014.1873
Di Angelantonio, Emanuele ; Gao, Pei ; Khan, Hassan ; Butterworth, Adam S. ; Wormser, David ; Kaptoge, Stephen ; Kondapally Seshasai, Sreenivasa Rao ; Thompson, Alex ; Sarwar, Nadeem ; Willeit, Peter ; Ridker, Paul M. ; Barr, Elizabeth L.M. ; Khaw, Kay Tee ; Psaty, Bruce M. ; Brenner, Hermann ; Balkau, Beverley ; Dekker, Jacqueline M. ; Lawlor, Debbie A. ; Daimon, Makoto ; Willeit, Johann ; Njølstad, Inger ; Nissinen, Aulikki ; Brunner, Eric J. ; Kuller, Lewis H. ; Price, Jackie F. ; Sundström, Johan ; Knuiman, Matthew W. ; Feskens, Edith J.M. ; Verschuren, W. M.M. ; Wald, Nicholas ; Bakker, Stephan J.L. ; Whincup, Peter H. ; Ford, Ian ; Goldbourt, Uri ; Gómez-de-la-Cámara, Agustín ; Gallacher, John ; Simons, Leon A. ; Rosengren, Annika ; Sutherland, Susan E. ; Björkelund, Cecilia ; Blazer, Dan G. ; Wassertheil-Smoller, Sylvia ; Onat, Altan ; Marín Ibañez, Alejandro ; Casiglia, Edoardo ; Jukema, J. Wouter ; Simpson, Lara M. ; Giampaoli, Simona ; Nordestgaard, Børge G. ; Selmer, Randi ; Wennberg, Patrik ; Kauhanen, Jussi ; Salonen, Jukka T. ; Dankner, Rachel ; Barrett-Connor, Elizabeth ; Kavousi, Maryam ; Gudnason, Vilmundur ; Evans, Denis ; Wallace, Robert B. ; Cushman, Mary ; D'Agostino, Ralph B. ; Umans, Jason G. ; Kiyohara, Yutaka ; Nakagawa, Hidaeki ; Sato, Shinichi ; Gillum, Richard F. ; Folsom, Aaron R. ; van der Schouw, Yvonne T. ; Moons, Karel G. ; Griffin, Simon J. ; Sattar, Naveed ; Wareham, Nicholas J. ; Selvin, Elizabeth ; Thompson, Simon G. ; Danesh, John ; The Emerging Risk Factors Collaboration. / Glycated hemoglobin measurement and prediction of cardiovascular disease. In: JAMA - Journal of the American Medical Association. 2014 ; Vol. 311, No. 12. pp. 1225-1233.
@article{cd6436934d9340c8976065a1ef2d03ac,
title = "Glycated hemoglobin measurement and prediction of cardiovascular disease",
abstract = "Importance: The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain.Objective: To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk.Design, Setting, and Participants: Analysis of individual-participant data available from 73 prospective studies involving 294 998 participants without a known history of diabetes mellitus or CVD at the baseline assessment.Main Outcomes and Measures: Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5{\%}), intermediate (5{\%} to <7.5{\%}), and high (≥7.5{\%}) risk.Results: During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20 840 incident fatal and nonfatal CVD outcomes (13 237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95{\%} CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (−0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels.Conclusions and Relevance: In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk.",
author = "{Di Angelantonio}, Emanuele and Pei Gao and Hassan Khan and Butterworth, {Adam S.} and David Wormser and Stephen Kaptoge and {Kondapally Seshasai}, {Sreenivasa Rao} and Alex Thompson and Nadeem Sarwar and Peter Willeit and Ridker, {Paul M.} and Barr, {Elizabeth L.M.} and Khaw, {Kay Tee} and Psaty, {Bruce M.} and Hermann Brenner and Beverley Balkau and Dekker, {Jacqueline M.} and Lawlor, {Debbie A.} and Makoto Daimon and Johann Willeit and Inger Nj{\o}lstad and Aulikki Nissinen and Brunner, {Eric J.} and Kuller, {Lewis H.} and Price, {Jackie F.} and Johan Sundstr{\"o}m and Knuiman, {Matthew W.} and Feskens, {Edith J.M.} and Verschuren, {W. M.M.} and Nicholas Wald and Bakker, {Stephan J.L.} and Whincup, {Peter H.} and Ian Ford and Uri Goldbourt and Agust{\'i}n G{\'o}mez-de-la-C{\'a}mara and John Gallacher and Simons, {Leon A.} and Annika Rosengren and Sutherland, {Susan E.} and Cecilia Bj{\"o}rkelund and Blazer, {Dan G.} and Sylvia Wassertheil-Smoller and Altan Onat and {Mar{\'i}n Iba{\~n}ez}, Alejandro and Edoardo Casiglia and Jukema, {J. Wouter} and Simpson, {Lara M.} and Simona Giampaoli and Nordestgaard, {B{\o}rge G.} and Randi Selmer and Patrik Wennberg and Jussi Kauhanen and Salonen, {Jukka T.} and Rachel Dankner and Elizabeth Barrett-Connor and Maryam Kavousi and Vilmundur Gudnason and Denis Evans and Wallace, {Robert B.} and Mary Cushman and D'Agostino, {Ralph B.} and Umans, {Jason G.} and Yutaka Kiyohara and Hidaeki Nakagawa and Shinichi Sato and Gillum, {Richard F.} and Folsom, {Aaron R.} and {van der Schouw}, {Yvonne T.} and Moons, {Karel G.} and Griffin, {Simon J.} and Naveed Sattar and Wareham, {Nicholas J.} and Elizabeth Selvin and Thompson, {Simon G.} and John Danesh and {The Emerging Risk Factors Collaboration}",
year = "2014",
month = "3",
day = "26",
doi = "10.1001/jama.2014.1873",
language = "English",
volume = "311",
pages = "1225--1233",
journal = "JAMA",
issn = "0098-7484",
publisher = "American Medical Association",
number = "12",

}

Di Angelantonio, E, Gao, P, Khan, H, Butterworth, AS, Wormser, D, Kaptoge, S, Kondapally Seshasai, SR, Thompson, A, Sarwar, N, Willeit, P, Ridker, PM, Barr, ELM, Khaw, KT, Psaty, BM, Brenner, H, Balkau, B, Dekker, JM, Lawlor, DA, Daimon, M, Willeit, J, Njølstad, I, Nissinen, A, Brunner, EJ, Kuller, LH, Price, JF, Sundström, J, Knuiman, MW, Feskens, EJM, Verschuren, WMM, Wald, N, Bakker, SJL, Whincup, PH, Ford, I, Goldbourt, U, Gómez-de-la-Cámara, A, Gallacher, J, Simons, LA, Rosengren, A, Sutherland, SE, Björkelund, C, Blazer, DG, Wassertheil-Smoller, S, Onat, A, Marín Ibañez, A, Casiglia, E, Jukema, JW, Simpson, LM, Giampaoli, S, Nordestgaard, BG, Selmer, R, Wennberg, P, Kauhanen, J, Salonen, JT, Dankner, R, Barrett-Connor, E, Kavousi, M, Gudnason, V, Evans, D, Wallace, RB, Cushman, M, D'Agostino, RB, Umans, JG, Kiyohara, Y, Nakagawa, H, Sato, S, Gillum, RF, Folsom, AR, van der Schouw, YT, Moons, KG, Griffin, SJ, Sattar, N, Wareham, NJ, Selvin, E, Thompson, SG, Danesh, J & The Emerging Risk Factors Collaboration 2014, 'Glycated hemoglobin measurement and prediction of cardiovascular disease', JAMA - Journal of the American Medical Association, vol. 311, no. 12, pp. 1225-1233. https://doi.org/10.1001/jama.2014.1873

Glycated hemoglobin measurement and prediction of cardiovascular disease. / Di Angelantonio, Emanuele; Gao, Pei; Khan, Hassan; Butterworth, Adam S.; Wormser, David; Kaptoge, Stephen; Kondapally Seshasai, Sreenivasa Rao; Thompson, Alex; Sarwar, Nadeem; Willeit, Peter; Ridker, Paul M.; Barr, Elizabeth L.M.; Khaw, Kay Tee; Psaty, Bruce M.; Brenner, Hermann; Balkau, Beverley; Dekker, Jacqueline M.; Lawlor, Debbie A.; Daimon, Makoto; Willeit, Johann; Njølstad, Inger; Nissinen, Aulikki; Brunner, Eric J.; Kuller, Lewis H.; Price, Jackie F.; Sundström, Johan; Knuiman, Matthew W.; Feskens, Edith J.M.; Verschuren, W. M.M.; Wald, Nicholas; Bakker, Stephan J.L.; Whincup, Peter H.; Ford, Ian; Goldbourt, Uri; Gómez-de-la-Cámara, Agustín; Gallacher, John; Simons, Leon A.; Rosengren, Annika; Sutherland, Susan E.; Björkelund, Cecilia; Blazer, Dan G.; Wassertheil-Smoller, Sylvia; Onat, Altan; Marín Ibañez, Alejandro; Casiglia, Edoardo; Jukema, J. Wouter; Simpson, Lara M.; Giampaoli, Simona; Nordestgaard, Børge G.; Selmer, Randi; Wennberg, Patrik; Kauhanen, Jussi; Salonen, Jukka T.; Dankner, Rachel; Barrett-Connor, Elizabeth; Kavousi, Maryam; Gudnason, Vilmundur; Evans, Denis; Wallace, Robert B.; Cushman, Mary; D'Agostino, Ralph B.; Umans, Jason G.; Kiyohara, Yutaka; Nakagawa, Hidaeki; Sato, Shinichi; Gillum, Richard F.; Folsom, Aaron R.; van der Schouw, Yvonne T.; Moons, Karel G.; Griffin, Simon J.; Sattar, Naveed; Wareham, Nicholas J.; Selvin, Elizabeth; Thompson, Simon G.; Danesh, John; The Emerging Risk Factors Collaboration.

In: JAMA - Journal of the American Medical Association, Vol. 311, No. 12, 26.03.2014, p. 1225-1233.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Glycated hemoglobin measurement and prediction of cardiovascular disease

AU - Di Angelantonio, Emanuele

AU - Gao, Pei

AU - Khan, Hassan

AU - Butterworth, Adam S.

AU - Wormser, David

AU - Kaptoge, Stephen

AU - Kondapally Seshasai, Sreenivasa Rao

AU - Thompson, Alex

AU - Sarwar, Nadeem

AU - Willeit, Peter

AU - Ridker, Paul M.

AU - Barr, Elizabeth L.M.

AU - Khaw, Kay Tee

AU - Psaty, Bruce M.

AU - Brenner, Hermann

AU - Balkau, Beverley

AU - Dekker, Jacqueline M.

AU - Lawlor, Debbie A.

AU - Daimon, Makoto

AU - Willeit, Johann

AU - Njølstad, Inger

AU - Nissinen, Aulikki

AU - Brunner, Eric J.

AU - Kuller, Lewis H.

AU - Price, Jackie F.

AU - Sundström, Johan

AU - Knuiman, Matthew W.

AU - Feskens, Edith J.M.

AU - Verschuren, W. M.M.

AU - Wald, Nicholas

AU - Bakker, Stephan J.L.

AU - Whincup, Peter H.

AU - Ford, Ian

AU - Goldbourt, Uri

AU - Gómez-de-la-Cámara, Agustín

AU - Gallacher, John

AU - Simons, Leon A.

AU - Rosengren, Annika

AU - Sutherland, Susan E.

AU - Björkelund, Cecilia

AU - Blazer, Dan G.

AU - Wassertheil-Smoller, Sylvia

AU - Onat, Altan

AU - Marín Ibañez, Alejandro

AU - Casiglia, Edoardo

AU - Jukema, J. Wouter

AU - Simpson, Lara M.

AU - Giampaoli, Simona

AU - Nordestgaard, Børge G.

AU - Selmer, Randi

AU - Wennberg, Patrik

AU - Kauhanen, Jussi

AU - Salonen, Jukka T.

AU - Dankner, Rachel

AU - Barrett-Connor, Elizabeth

AU - Kavousi, Maryam

AU - Gudnason, Vilmundur

AU - Evans, Denis

AU - Wallace, Robert B.

AU - Cushman, Mary

AU - D'Agostino, Ralph B.

AU - Umans, Jason G.

AU - Kiyohara, Yutaka

AU - Nakagawa, Hidaeki

AU - Sato, Shinichi

AU - Gillum, Richard F.

AU - Folsom, Aaron R.

AU - van der Schouw, Yvonne T.

AU - Moons, Karel G.

AU - Griffin, Simon J.

AU - Sattar, Naveed

AU - Wareham, Nicholas J.

AU - Selvin, Elizabeth

AU - Thompson, Simon G.

AU - Danesh, John

AU - The Emerging Risk Factors Collaboration

PY - 2014/3/26

Y1 - 2014/3/26

N2 - Importance: The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain.Objective: To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk.Design, Setting, and Participants: Analysis of individual-participant data available from 73 prospective studies involving 294 998 participants without a known history of diabetes mellitus or CVD at the baseline assessment.Main Outcomes and Measures: Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5% to <7.5%), and high (≥7.5%) risk.Results: During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20 840 incident fatal and nonfatal CVD outcomes (13 237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (−0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels.Conclusions and Relevance: In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk.

AB - Importance: The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain.Objective: To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk.Design, Setting, and Participants: Analysis of individual-participant data available from 73 prospective studies involving 294 998 participants without a known history of diabetes mellitus or CVD at the baseline assessment.Main Outcomes and Measures: Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5% to <7.5%), and high (≥7.5%) risk.Results: During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20 840 incident fatal and nonfatal CVD outcomes (13 237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (−0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels.Conclusions and Relevance: In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk.

UR - http://www.scopus.com/inward/record.url?scp=84896675182&partnerID=8YFLogxK

U2 - 10.1001/jama.2014.1873

DO - 10.1001/jama.2014.1873

M3 - Article

VL - 311

SP - 1225

EP - 1233

JO - JAMA

JF - JAMA

SN - 0098-7484

IS - 12

ER -

Di Angelantonio E, Gao P, Khan H, Butterworth AS, Wormser D, Kaptoge S et al. Glycated hemoglobin measurement and prediction of cardiovascular disease. JAMA - Journal of the American Medical Association. 2014 Mar 26;311(12):1225-1233. https://doi.org/10.1001/jama.2014.1873