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The Fallacy of Average: How Using HbA1c Alone to Assess Glycemic Control Can Be Misleading

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Beck, Roy W., Connor, Crystal G., Mullen, Deborah M., Wesley, David M., Bergenstal, Richard M.·2017·Diabetes Care

DOI 10.2337/dc17-0636PMC PMC5521971

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Abstract

HbA1c is a valuable metric for comparing treatment groups in a randomized trial, for assessing glycemic trends in a population over time, or for cross-sectional comparisons of glycemic control in different populations. However, what is not widely appreciated is that HbA1c may not be a good indicator of an individual patient’s glycemic control because of the wide range of mean glucose concentrations and glucose profiles that can be associated with a given HbA1c level. To illustrate this point, we plotted mean glucose measured with continuous glucose monitoring (CGM) versus central laboratory–measured HbA1c in 387 participants in three randomized trials, showing that not infrequently HbA1c may underestimate or overestimate mean glucose, sometimes substantially. Thus, if HbA1c is to be used to assess glycemic control, it is imperative to know the patient’s actual mean glucose to understand how well HbA1c is an indicator of the patient’s glycemic control. With knowledge of the mean glucose, an estimated HbA1c (eA1C) can be calculated with the formula provided in this article to compare with the measured HbA1c. Estimating glycemic control from HbA1c alone is in essence applying a population average to an individual, which can be misleading. Thus, a patient’s CGM glucose profile has considerable value for optimizing his or her diabetes management. In this era of personalized, precision medicine, there are few better examples with respect to the fallacy of applying a population average to a specific patient rather than using specific information about the patient to determine the optimal approach to treatment.

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Translating the A1C assay into estimated average glucose values
Nathan, D. M., Kuenen, J., Borg, R., Zheng, H., Schoenfeld, D., Heine, R. J., & for the A1c-Derived Average Glucose (ADAG) Study Group (2008) · Diabetes Care · doi:10.2337/dc08-0545 · Cited by 1,812
Effect of Continuous Glucose Monitoring on Glycemic Control in Adults With Type 1 Diabetes Using Insulin Injections: The DIAMOND Randomized Clinical Trial
Beck, R. W., Riddlesworth, T., Ruedy, K., Ahmann, A., Bergenstal, R., Haller, S., Kollman, C., Kruger, D., McGill, J. B., Polonsky, W., et al. (2017) · JAMA · doi:10.1001/jama.2016.19975 · Cited by 1,185
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Defining the Relationship Between Plasma Glucose and HbA1c
Rohlfing, C. L., Wiedmeyer, H.-M., Little, R. R., England, J. D., Tennill, A., & Goldstein, D. E. (2002) · Diabetes Care · doi:10.2337/diacare.25.2.275 · Cited by 987
Continuous Glucose Monitoring Versus Usual Care in Patients With Type 2 Diabetes Receiving Multiple Daily Insulin Injections: A Randomized Trial
Beck, R. W., Riddlesworth, T. D., Ruedy, K., Ahmann, A., Haller, S., Kruger, D., McGill, J. B., Polonsky, W., Price, D., Aronoff, S., et al. (2017) · Annals of Internal Medicine · doi:10.7326/m16-2855 · Cited by 635
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Red cell life span heterogeneity in hematologically normal people is sufficient to alter HbA1c
Cohen, R. M., Franco, R. S., Khera, P. K., Smith, E. P., Lindsell, C. J., Ciraolo, P. J., Palascak, M. B., & Joiner, C. H. (2008) · Blood · doi:10.1182/blood-2008-04-154112 · Cited by 481
REPLACE-BG: a randomized trial comparing continuous glucose monitoring with and without routine blood glucose monitoring in adults with well-controlled type 1 diabetes
Aleppo, G., Ruedy, K. J., Riddlesworth, T. D., Kruger, D. F., Peters, A. L., Hirsch, I., Bergenstal, R. M., Toschi, E., Ahmann, A. J., Shah, V. N., et al. (2017) · Diabetes Care · doi:10.2337/dc16-2482 · Cited by 329
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High and low hemoglobin glycation phenotypes in type 1 diabetes
Hempe, J. M., Gómez, R., McCarter, R., & Chalew, S. A. (2002) · Journal of Diabetes and its Complications · doi:10.1016/s1056-8727(01)00227-6 · Cited by 322
Recommendations for standardizing glucose reporting and analysis to optimize clinical decision making in diabetes: the Ambulatory Glucose Profile (AGP)
Bergenstal, R. M., Ahmann, A. J., Bailey, T., Beck, R. W., Bissen, J., Buckingham, B., Deeb, L., Dolin, R. H., Garg, S. K., Goland, R., et al. (2013) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2013.0051 · Cited by 307
Self-citation
Racial Differences in the Relationship of Glucose Concentrations and Hemoglobin A1c Levels
Bergenstal, R. M., Gal, R. L., Connor, C. G., Gubitosi-Klug, R., Kruger, D., Olson, B. A., Willi, S. M., Aleppo, G., Weinstock, R. S., Wood, J., et al. (2017) · Annals of Internal Medicine · doi:10.7326/m16-2596 · Cited by 306
Self-citation
The Hemoglobin Glycation Index Identifies Subpopulations With Harms or Benefits From Intensive Treatment in the ACCORD Trial
Hempe, J. M., Liu, S., Myers, L., McCarter, R., Buse, J. B., & Fonseca, V. A. (2015) · Diabetes Care · doi:10.2337/dc14-1844 · Cited by 238

Show all 29 references

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Authors: Beck, R. W., Connor, C. G., Mullen, D. M., Wesley, D. M., & Bergenstal, R. M.
Affiliations: Jaeb Center for Health Research (US)
Park Nicollet Health Services (US)
Corresponding author: Beck, Roy W.
ORCID: Beck, Roy W.
Mullen, Deborah M.
Bergenstal, Richard M.
Venue: Diabetes Care
Publisher: American Diabetes Association
Published: 2017-07-11
Volume: 40
Issue: 8
Pages: 994-999
ISSN: 0149-5992 (ISSN-L)
1935-5548
DOI: 10.2337/dc17-0636
PMC: PMC5521971
OpenAlex: W2739310415
Cited by: 477
References: 29
Citations by year: 2026: 44 · 2025: 47 · 2024: 62 · 2023: 48 · 2022: 67 · 2021: 75 · 2020: 56 · 2019: 43 · 2018: 28 · 2017: 7
FWCI: 28.99
Type: journal article
Language: en
Open access: green
europepmc.org
Licence: www.diabetesjournals.org/content/license (vor, 10 d)
Locations: Diabetes Care (publishedVersion)
Europe PMC (PubMed Central) (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Funders: Leona M. and Harry B. Helmsley Charitable Trust
The National Institute of Diabetes and Digestive and Kidney Diseases (DK108611)
Topics: Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
Keywords: HbA1c, glycemic control, mean blood glucose, continuous glucose monitoring, HbA1c estimation, diabetes management, personalized medicine, glucose profile
MeSH terms: Adult, Aged, Blood Glucose, Cross-Sectional Studies, Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2, Female, Glycated Hemoglobin, Humans, Male, Middle Aged, Blood Glucose Self-Monitoring, Disease Management, Young Adult, Precision Medicine

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The Fallacy of Average: How Using HbA1c Alone to Assess Glycemic Control Can Be Misleading

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