The fallacy of average: how using HbA1c alone to assess glycemic control can be misleading
Open accessAbstract
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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The variability of mean glucose at the same HbA1c is similar to what has been observed in the T1D population and highlights the limitation of HbA1c to reflect true glycemic status for some individuals.
“This is similar to what has been observed in the T1D population and highlights the limitation of HbA1c to reflect true glycemic status for some individuals (14).”
From Continuous Glucose Monitoring Profiles in Healthy Nondiabetic Participants: A Multicenter Prospective Study (2019) · cites this paper as [14]
As assessment of diabetes treatment outcomes moves beyond HbA1c to include sensor glucose profiles, there is an increased need for a repository of normative CGM data with up-to-date and widely used devices.
“As the assessment of outcomes of treatment of T1D and type 2 diabetes in clinical practice and research trials moves beyond the narrow focus of HbA1c levels to include the results of sensor glucose profiles (14), there is an increased need for a repository of”
From Continuous Glucose Monitoring Profiles in Healthy Nondiabetic Participants: A Multicenter Prospective Study (2019) · cites this paper as [14]
HbA1c is inappropriate as the only method of glucose evaluation in type 1 diabetes.
“Although HbA 1c is an indicator of mean glucose, it does not inform glycemic variability and hypoglycemia and, therefore, is inappropriate as the only method of glucose evaluation in type 1 diabetes (68,69).”
Within an individual, HbA1c and blood glucose correlate over time.
“Variability exists between individuals, but the HbA 1c and blood glucose within an individual correlate over time (68).”
HbA1c does not inform glycemic variability and hypoglycemia.
“Although HbA 1c is an indicator of mean glucose, it does not inform glycemic variability and hypoglycemia and, therefore, is inappropriate as the only method of glucose evaluation in type 1 diabetes (68,69).”
In a report, mean glucose measured with CGM versus central laboratory-measured A1C in 387 participants in three randomized trials demonstrated that A1C may underestimate or overestimate mean glucose in individuals.
“In a report, mean glucose measured with CGM versus central laboratory-measured A1C in 387 participants in three randomized trials demonstrated that A1C may underestimate or overestimate mean glucose in individuals (12).”
From 6. Glycemic Targets: <i>Standards of Care in Diabetes—2023</i> (2023) · cites this paper as [12]
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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.
- 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
- 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
- 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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