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 WilleitInger 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 journalArticlepeer-review


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
Issue number12
Publication statusPublished - 26 Mar 2014
Externally publishedYes


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