Glucose Management Indicator Replaces eA1c in Patients with CGM Sensors

Validation of the Glucose Management Indicator (GMI) as an acceptable replacement for “estimated HbA1c” in patients using continuous glucose monitoring grows with the endorsement of the FDA.

By Richard M. Bergenstal, MD,  and David W. Lam, MD

Hemoglobin A1c (HbA1c) has been the established marker for diabetes complications since the mid-1970s, and has been the primary factor used to inform treatment changes. Continuous glucose monitoring (CGM) systems, which are growing in use, provide a robust depth of information about a patient's diabetes-related metrics. The data obtained from CGMs was originally converted into an “estimated HbA1c (eA1c)” values but this caused confusion as the eA1c was different than the lab values for HbA1c. This made informed treatment planning more problematic—the question arose: Which value to trust? The Food and Drug Administration stepped in, requiring removal of eA1c values from CGM devices.

Recognizing the accuracy of CGM data, and the need for a representative term generated by these devices, Bergenstal and an esteemed group of endocrine experts went about developing a new value—the glucose management indicator (GMI)—to represent the mean glucose trends based on reported CGM trends data.The GMI is calculated using the formula GMI (%) = 3.31 + 0.02392 x mean glucose in mg/dL.  

CGM generated HbA1c values are more closely aligned to patient blood glucose.

Verifying Functionality of Glucose Management Indicator  

Initially validated using data collected from Dexcom glucose sensors,1 these investigators then sought to extend the functionality of the GMI to two other commonly used continuous glucose monitoring sensors: Guardian Sensor 3 (Medtronic) and the Freestyle Navigator II (Abbott);their findings appear in Diabetes Care.

To verify the GMI in these CGMs, the researchers set about deriving mean glucose values from pooled data collected from three recent randomized clinical trials in both children and adults with T1D:

  • Home testing of day and night closed loop with pump suspend feature (APCam11 using Guardian 3)3
  • Closing the loop in adults with sub-optimally controlled type 1 diabetes under free-living conditions (AP@ome04 using Navigator 2)4
  • Closing the loop in children and adolescents with type 1 diabetes in the home setting {APCam08, Navigator 2)4

The data was then compared with the calculations derived from the Dexcom study.1 Across the trials, the percentage of individuals with similar GMI and laboratory HbA1c, with an absolute difference of < 0.1%, was comparable at about 20%; this study provided further validation of the formula for determining GMI.

Another key finding from both validation studies were the substantial numbers of individuals with type 1 diabetes who had clinically meaningful differences between their laboratory-derived HbA1c and their sensor-derived GMI.1,2

“It is important for clinicians to pay attention to these disparities, and perhaps consider the individual’s GMI before making treatment revisions, as [this value] provides a more personalized picture of the patient’s glucose fluctuations over time,” said Richard M. Bergenstal, MD, executive director of the International Diabetes Center in Minneapolis, Minnesota, and a past president of the American Diabetes Association, in an interview with EndocrineWeb.

Insights on the Evolving Values Used for Blood Glucose Trends 

Questions about the utility of HbA1c as the standard index used in managing diabetes—primarily in patients with type 1 diabetes (T1D) but more frequently for insulin-dependent type 2 diabetes—have escalated with the increasing reliance on CGM.

More so, CGM technology has evolved such that the units are portable, factory calibrated thereby eliminating the need for glucose fingerstick checks, and more accurate, and which are more often covered by health insurance, removing cost as a delimiting factor.5

The GMI provides both patient and clinicians with a more robust depth of information on individual diabetes-related metrics, including patterns of hypoglycemia, hyperglycemia, and glucose variability, and most telling—glucose time in target range,1 said Dr. Bergenstal.

In a unique response to the proposal of the GMI, the FDA commended this new value, noting the GMI establishes an “important step for the proper use of the metric and that the inclusion of GMI in certain diabetes management devices (eg, software) could potentially offer additional insight into glycemic control.”6,7

Assessing Patients More Accurately for Complications of Diabetes

While HbA1c continues to be an “important population metric closely associated with diabetes-related vascular complications,” GMI offers a “more personalized approach to diabetes management”, Dr. Bergenstal told EndocrineWeb. Specifically, the GMI may provide a “better reflection of an individual’s average glucose variability, including time in target range and patterns of hypo- or hyperglycemia.”

“Until recently, we had the most (almost all) data from an individual’s A1c level,” David W. Lam, MD, assistant professor, Division of Endocrinology, Diabetes and Bone Diseases at the Icahn School of Medicine at Mount Sinai in New York, NY, told EndocrineWeb; he was not involved in the research.

Referring to a growing “Beyond A1c” movement in the diabetes field, Dr. Lam explained that for a long time, “A1c was the only snapshot of what was happening to a patient over the last three months. However, we don’t know if an HbA1c is actually reflective of what happened to that specific person.”

In other words, are there no clinically meaningful differences between two patients with the same HbA1c? The GMI appears to provide a more robust description of an individual patient’s diabetes journey, enabling clinicians to make treatment decisions based on a greater wealth of data.1

Dr. Bergenstal also addressed the challenges that arise when assessing a patient's status given a greater amount of data. Specifically, clinicians and patients need to gain an understanding of the limitations of data used in formulating an individual's GMI. We need to develop a proper context for how the data fits with our current knowledge, and how it might be best applied in considering treatment decisions to optimally become another tool for the effective management of diabetes, he said.

“We can look at the GMI data and see how fluctuations might be influencing a patient’s quality of life; however, there is, as yet, still no standard of medical care outside of A1c.," said Dr. Lam.

The trials were supported by funding from the Juvenile Diabetes Research Fund JDRF and the Seventh Framework Program of the European Union with additional funding awarded to Dr. by the National Institute of Diabetes and Digestive and Kidney Disease.   Medtronic and Abbott Diabetes Care provided discounted sensors for clinical trials.

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Clinical Takeaways: Microvascular Risk, Metabolic Disease, Continuous Glucose Monitoring
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