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. 2014 Mar 26;311(12):1225-33.
doi: 10.1001/jama.2014.1873.

Glycated hemoglobin measurement and prediction of cardiovascular disease

Emerging Risk Factors CollaborationEmanuele Di Angelantonio  1 Pei Gao  1 Hassan Khan  1 Adam S Butterworth  1 David Wormser  1 Stephen Kaptoge  1 Sreenivasa Rao Kondapally Seshasai  2 Alex Thompson  1 Nadeem Sarwar  1 Peter Willeit  1 Paul M Ridker  3 Elizabeth L M Barr  4 Kay-Tee Khaw  1 Bruce M Psaty  5 Hermann Brenner  6 Beverley Balkau  7 Jacqueline M Dekker  8 Debbie A Lawlor  9 Makoto Daimon  10 Johann Willeit  11 Inger Njølstad  12 Aulikki Nissinen  13 Eric J Brunner  14 Lewis H Kuller  15 Jackie F Price  16 Johan Sundström  17 Matthew W Knuiman  18 Edith J M Feskens  19 W M M Verschuren  20 Nicholas Wald  21 Stephan J L Bakker  22 Peter H Whincup  2 Ian Ford  23 Uri Goldbourt  24 Agustín Gómez-de-la-Cámara  25 John Gallacher  26 Leon A Simons  27 Annika Rosengren  28 Susan E Sutherland  29 Cecilia Björkelund  30 Dan G Blazer  31 Sylvia Wassertheil-Smoller  32 Altan Onat  33 Alejandro Marín Ibañez  34 Edoardo Casiglia  35 J Wouter Jukema  36 Lara M Simpson  37 Simona Giampaoli  38 Børge G Nordestgaard  39 Randi Selmer  40 Patrik Wennberg  41 Jussi Kauhanen  42 Jukka T Salonen  43 Rachel Dankner  44 Elizabeth Barrett-Connor  45 Maryam Kavousi  46 Vilmundur Gudnason  47 Denis Evans  48 Robert B Wallace  49 Mary Cushman  50 Ralph B D'Agostino Sr  51 Jason G Umans  52 Yutaka Kiyohara  53 Hidaeki Nakagawa  54 Shinichi Sato  55 Richard F Gillum  56 Aaron R Folsom  57 Yvonne T van der Schouw  58 Karel G Moons  58 Simon J Griffin  1 Naveed Sattar  23 Nicholas J Wareham  1 Elizabeth Selvin  59 Simon G Thompson  1 John Danesh  1
Collaborators, Affiliations

Glycated hemoglobin measurement and prediction of cardiovascular disease

Emerging Risk Factors Collaboration et al. JAMA. .

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.

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Figures

Figure 1
Figure 1. Hazard Ratios for Incident Cardiovascular Disease (CVD) Outcomes by Baseline Levels of Glycemia Measures
Analyses were adjusted for age, smoking status, systolic blood pressure, total cholesterol level, and high-density lipoprotein cholesterol level and stratified by sex and trial group where appropriate. Participants were classified into groups of (1) HbA1c% (mmol/mol): <4.5 (<25.7), 4.5 to <5 (25.7-<31.1), 5 to <5.5 (31.1-<36.3) [reference category], 5.5 to <6 (36.6-<42.1), 6 to <6.5 (42.1-<48.0), and ≥6.5 (≥48.0); (2) fasting glucose (mg/dL): <76, 76 to <90, 90 to <105 [reference category], 105 to <119, 119 to <133, ≥133; (3) random glucose (mg/dL) <68, 68 to <90, 90 to <112 [reference category], 112 to <133, 133 to <155, ≥155; (4) Postload glucose (mg/dL): <68, 68 to <108, 108 to <148 [reference category], 148 to <187, 187 to <227, ≥227. These categories approximately correspond to 1-SD increments for each factor. Incident CVD outcomes refer to first-onset CVD cases, defined as fatal or nonfatal coronary heart disease or any stroke. SI conversion factors: To convert glucose values to mmol/L, multiply by 0.0555. Sizes of boxes are proportional to the inverse of the variance.
Figure 2
Figure 2. Hazard Ratios for Incident Cardiovascular Disease for Glycemia Measures by Selected Study-Level Characteristics
Participants with levels of glycemia measures below the mean were excluded. Baseline SD was used to calculate per-SD hazard ratio (HR). Analyses were conducted using studies with information across all levels of each subgroup variable. DCCT indicates Diabetes Control and Complications Trial; HPLC, high-performance liquid chromatography; ITA, immunoturbidimetric assay. A full list of the characteristics examined for heterogeneity is provided in eFigures 5 through 8 in Supplement.
Figure 3
Figure 3. Changes in Cardiovascular Disease Risk Discrimination After the Addition of Information on Glycemia Measures to Conventional Risk Factors
Incident cardiovascular disease outcomes refer to first-onset cardiovascular disease cases, defined as fatal or nonfatal coronary heart disease event or any stroke. Studies with missing self-reported diabetes information were excluded. a Conventional risk factors include age, sex (stratified), smoking status, systolic blood pressure, and levels of total cholesterol and high-density lipoprotein cholesterol. b P < .05 c P < .001.

References

    1. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2013;36(suppl 1):S67–S74. - PMC - PubMed
    1. Rydén L, Grant PJ, Anker SD, et al. Authors/Task Force Members; ESC Committee for Practice Guidelines (CPG); Document Reviewers. ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD: the Task Force on diabetes, pre-diabetes, and cardiovascular diseases of the European Society of Cardiology (ESC) and developed in collaboration with the European Association for the Study of Diabetes (EASD) Eur Heart J. 2013;34(39):3035–3087. - PubMed
    1. Selvin E, Steffes MW, Zhu H, et al. Glycated hemoglobin, diabetes, and cardiovascular risk in nondiabetic adults. N Engl J Med. 2010;362(9):800–811. - PMC - PubMed
    1. Sarwar N, Gao P, Seshasai SR, et al. Emerging Risk Factors Collaboration. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet. 2010;375(9733):2215–2222. published correction appears in Lancet. 2010;376(9745):958. - PMC - PubMed
    1. US Preventive Services Task Force. Using nontraditional risk factors in coronary heart disease risk assessment: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med. 2009;151(7):474–482. - PubMed

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