HbA(1c) is a valuablemetric 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 HbA(1c) 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 HbA(1c) level. To illustrate this point, we plotted mean glucose measured with continuous glucose monitoring (CGM) versus central laboratory-measured HbA(1c) in 387 participants in three randomized trials, showing that not infrequently HbA(1c) may underestimate or overestimate mean glucose, sometimes substantially. Thus, if HbA(1c) is to be used to assess glycemic control, it is imperative to know the patient's actual mean glucose to understand how well HbA(1c) is an indicator of the patient's glycemic control. With knowledge of the mean glucose, an estimated HbA(1c) (eA1C) can be calculated with the formula provided in this article to compare with the measured HbA(1c). Estimating glycemic control from HbA(1c) 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.
