Glycated hemoglobin measurement and prediction of cardiovascular disease
Open accessAbstract
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.
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Data from 73 studies on 294,998 individuals without known diabetes suggest that HbA1c is as good as or better than fasting, random, or post-load glucose levels for predicting cardiovascular risk.
“It should be noted that data from 73 studies on 294 998 individuals without known diabetes suggest that HbA1c is as good as or better than fasting, random, or post-load glucose levels for predicting CV risk.14”
From 2023 ESC guidelines for the management of cardiovascular disease in patients with diabetes. (2023) · cites this paper as [14]
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“Glycated hemoglobin (HbA1c) is a reliable measure of the mean levels of glucose concentration over 2–3 months before the onset of the acute illness [15, 16].”
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“Presently, most biomarkers used for evaluation of diabetes severity and progression, rely on metabolic parameters and are limited in improving risk stratification regarding disease-related outcomes [74].”
BackgroundMechanisms of Risk Reduction in the Clinical Practice of Alzheimer’s Disease Prevention
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“The latter contrasts with the meta-analysis of the ERFC that observed a significantly increased cardiovascular risk in subjects with an HbA1c <4.5 % (<26 mmol/mol) (HR 1.23 [1.02; 1.50]) compared with subjects with an HbA1c of 5 to <5.5 % (31 to <37 mmol/mol).”
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“complications, but is also the risk factor for other noncommunicable diseases including cardiovascular disease and cancer [3–5].”
BackgroundHemoglobin A1c Levels and the Risk of Cardiovascular Disease in People Without Known Diabetes
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“27 The Emerging Risk Factors Collaboration pooled analysis excluded patients with a known history of diabetes or CVD at baseline and categorized 101 280 participants according to 0.5% increments of HbA1c (from 4.5% to ≥6.5%).”
InfluentialImpact of Diabetes Mellitus on Stroke and Survival in Patients With Atrial Fibrillation
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“Likewise, a recent study showed that assessment of A1C values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk (16).”
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“2% reduction in HbA1c significantly reduces the risk of mortality by 10% [25].”
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“Growing evidence supports the finding that HbA1c level is an independent risk factor for cardiovascular events, regardless of the diagnosis of diabetes.(17-20)”
Hyperglycemia: a bad signature on the vascular system.
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“Interestingly, a very recent study conducted on individuals without known CVD or diabetes, additional assessment of HbA1c values provided incremental benefit for prediction of CVD risk (5).”
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“Nonetheless, data from the Emerging Risk Factors Collaboration revealed that HbA1c merely added little incremental benefit for ASCVD risk prediction in patients without known ASCVD and diabetes [12].”
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“7% (8 mmol/mol) represents a significant improvement in control.(16,17) The results of this study indicate that DSMS HTK participants are able to improve glycemic control regardless of the number of classes they attend, and they may experience an additional reduction in A1C with more frequent HTK participation.”
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“The Emerging Risk Factors Collaboration study suggested a J-shaped association of HbA1c with incident CVD [3], whilst another study suggests a threshold relationship of HbA1c (≥53 mmol/mol, 7.0”
BackgroundInfluentialSerum cystatin C for risk stratification of prediabetes and diabetes populations
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Is Corneal Arcus Independently Associated With Incident Cardiovascular Disease in Asians?
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“This notion, however, was not supported by a recent systematic review (6), where associations and risk prediction for CVD were similar for HbA1c, FPG, and 2hPG, although joint evaluation of these measures was not possible.”
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- Authors
- Di Angelantonio, E., Gao, P., Khan, H., Butterworth, A. S., Wormser, D., Kaptoge, S., Kondapally Seshasai, S. R., Thompson, A., Sarwar, N., Willeit, P., Ridker, P. M., Barr, E. L. M., Khaw, K.-T., Psaty, B. M., Brenner, H., Balkau, B., Dekker, J. M., Lawlor, D. A., Daimon, M., Willeit, J., Njølstad, I., Nissinen, A., Brunner, E. J., Kuller, L. H., Price, J. F., Sundström, J., Knuiman, M. W., Feskens, E. J. M., Verschuren, W. M. M., Wald, N., Bakker, S. J. L., Whincup, P. H., Ford, I., Goldbourt, U., Gómez-de-la-Cámara, A., Gallacher, J., Simons, L. A., Rosengren, A., Sutherland, S. E., Björkelund, C., Blazer, D. G., Wassertheil-Smoller, S., Onat, A., Marín Ibañez, A., Casiglia, E., Jukema, J. W., Simpson, L. M., Giampaoli, S., Nordestgaard, B. G., Selmer, R., Wennberg, P., Kauhanen, J., Salonen, J. T., Dankner, R., Barrett-Connor, E., Kavousi, M., Gudnason, V., Evans, D., Wallace, R. B., Cushman, M., D’Agostino, R. B., Umans, J. G., Kiyohara, Y., Nakagawa, H., Sato, S., Gillum, R. F., Folsom, A. R., van der Schouw, Y. T., Moons, K. G., Griffin, S. J., Sattar, N., Wareham, N. J., Selvin, E., Thompson, S. G., & Danesh, J.
- Affiliations
- University of Cambridge, Cambridge, United Kingdom
- University of Cambridge (GB)
- St George's University of London, London, United Kingdom
- Brigham and Women's Hospital (US)
- Baker Heart and Diabetes Institute (AU)
- University of Washington (US)
- German Cancer Research Center (DE)
- Inserm (FR)
- Amsterdam UMC Location Vrije Universiteit Amsterdam (NL)
- University of Bristol (GB)
- Yamagata University (JP)
- Innsbruck Medical University (AT)
- UiT The Arctic University of Norway (NO)
- Finnish Institute for Health and Welfare (FI)
- University College London (GB)
- University of Pittsburgh (US)
- University of Edinburgh (GB)
- Uppsala University (SE)
- The University of Western Australia (AU)
- Wageningen University & Research (NL)
- National Institute for Public Health and the Environment (NL)
- Wolfson Institute of Preventive Medicine, London, United Kingdom
- University Medical Center Groningen (NL)
- St George's, University of London (GB)
- University of Glasgow (GB)
- Sheba Medical Center (IL)
- Hospital 12 de Octubre, Madrid, Spain
- Cardiff University (GB)
- UNSW Sydney (AU)
- University of Gothenburg (SE)
- Medical University of South Carolina (US)
- Duke Medical Center (US)
- Albert Einstein College of Medicine, New York, New York
- Istanbul University (TR)
- San Jose Norte Health Centre, Zaragoza, Spain
- University of Padua (IT)
- Leiden University Medical Center (NL)
- University of Texas School of Public Health, Houston
- Istituto Superiore di Sanità (IT)
- University of Copenhagen (DK)
- Norwegian Institute of Public Health (NO)
- Umeå University (SE)
- University of Eastern Finland (FI)
- University of Helsinki (FI)
- Feinstein Institute for Medical Research (US)
- University of California San Diego (US)
- Erasmus MC (NL)
- University of Iceland (IS)
- Rush University Medical Center (US)
- University of Iowa (US)
- University of Vermont (US)
- Boston University (US)
- Georgetown University (US)
- Kyushu University (JP)
- Kanazawa Medical University (JP)
- Chiba Prefectural Institute of Public Health (JP)
- Howard University (US)
- University of Minnesota (US)
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
- University Medical Center Utrecht (NL)
- Johns Hopkins University (US)
- Corresponding author
- Danesh, John
- ORCID
- Gao, Pei
- Khan, Hassan
- Butterworth, Adam S.
- Kaptoge, Stephen
- Thompson, Alex
- Sarwar, Nadeem
- Willeit, Peter
- Ridker, Paul M
- Barr, Elizabeth L. M.
- Khaw, Kay-Tee
- Psaty, Bruce M.
- Brenner, Hermann
- Balkau, Beverley
- Lawlor, Debbie A.
- Daimon, Makoto
- Willeit, Johann
- Njølstad, Inger
- 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
- Gallacher, John
- Simons, Leon A.
- Rosengren, Annika
- Sutherland, Susan E.
- Blazer, Dan G.
- Onat, Altan
- Casiglia, Edoardo
- Jukema, J. Wouter
- Giampaoli, Simona
- Nordestgaard, Børge G.
- Selmer, Randi
- Wennberg, Patrik
- Dankner, Rachel
- Barrett-Connor, Elizabeth
- Kavousi, Maryam
- Gudnason, Vilmundur
- Evans, Denis
- Wallace, Robert B.
- Cushman, Mary
- D’Agostino, Ralph B.
- Umans, Jason G.
- Sato, Shinichi
- Gillum, Richard F.
- Folsom, Aaron R.
- Moons, Karel G.
- Griffin, Simon J.
- Sattar, Naveed
- Wareham, Nicholas J.
- Selvin, Elizabeth
- Thompson, Simon G.
- Danesh, John
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2014-03-26
- Volume
- 311
- Issue
- 12
- Pages
- 1225
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- PMC
- PMC4386007
- OpenAlex
- W2114008139
- Cited by
- 231
- References
- 32
- Citations by year
- 2026: 10 · 2025: 12 · 2024: 17 · 2023: 12 · 2022: 20 · 2021: 14 · 2020: 22 · 2019: 13 · 2018: 20 · 2017: 22 · 2016: 23 · 2015: 34 · 2014: 12
- FWCI
- 24.27
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- JAMA (publishedVersion)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Socio-Environmental Systems Modeling (acceptedVersion)
- UWA Profiles and Research Repository (UWA) (submittedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion)
- Rivm Repository (Netherlands National Institute for Public Health and the Environment) (submittedVersion)
- STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) (submittedVersion)
- Padua Research Archive (University of Padova) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- National Institute for Health and Care Research (NF-SI-0512-10165, NF-SI-0512-10114)
- British Heart Foundation (RG/08/013/25942, RG/13/16/30528, PG/13/66/30442, RG/08/014/24067)
- National Institutes of Health (UL1TR000062)
- Medical Research Council (MC_UU_12015/4, MR/K013351/1, MR/L003120/1)
- National Center for Advancing Translational Sciences
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Keywords
- HbA1c, cardiovascular risk prediction, coronary artery disease, stroke, risk discrimination, net reclassification improvement, cardiovascular risk factors, J-shaped association, fasting blood glucose, post-load glucose, C-reactive protein, HDL cholesterol, estimated glomerular filtration rate, non-diabetic adults
- MeSH terms
- Aged, C-Reactive Protein, Coronary Disease, Diabetes Mellitus, Female, Glycated Hemoglobin, Humans, Cholesterol, HDL, Male, Middle Aged, Predictive Value of Tests, Prospective Studies, Risk Assessment, Stroke
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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