Posted Oct 4 , 2017 09:12 AM

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

Beck RW, et al. Diabetes Care 2017;40:994

What is this perspective article about (excerpted from the Abstract)?

A1C 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 A1C 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 A1C 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 A1C may underestimate or overestimate mean glucose, sometimes substantially. Thus, if A1C is to be used to assess glycemic control, it is imperative to know the patient’s actual mean glucose to understand how well A1C is an indicator of the patient’s glycemic control. With knowledge of the mean glucose, an estimated A1C (eA1C) can be calculated with the formula provided in this article to compare with the measured A1C. Estimating glycemic control from A1C alone is 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.

Why is this important?

Hemoglobin A1c has been established as a ‘gold standard’ for assessment of outcomes in clinical trials, yet in the last few years it has been recognized as not providing enough information to make the best treatment decisions or, for that matter, to assess improvements in glycemic control. Time-in-range assessments of glucose control have significant added value (J Diabetes Sci Technol. 2015;9(1):56-62) in people with diabetes and have also been associated with outcomes in critically ill people without diabetes (Crit Care. 2015;19:179). With the endorsement of expanded use of CGM (Endocr Pract. 2016;22(8):1008-21), and with the recent reimbursement decisions on “therapeutic CGM” by CMS ( there will likely be a steady increase in the number of people using this technology, and other similar technologies to measure glucose on a continuous or near continuous basis. Becoming more familiar with the use of time-in-range, and the graphic representations of various glucose measurements or calculations should improve our abilities to better personalize diabetes management treatments whether they be diet, exercise or medications. Do you use CGM in in your practice? Do you use “time-in-range’ to help manage or motivate your patients?

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