Blood Glucose Control Metrics
Hemoglobin A1c (HbA1c or A1c), a test that measures a person’s blood-glucose levels over the past several months, is a key blood glucose control metric, or analytical measurement, used today in Type 1 Diabetes (T1D) management. But since it reflects an average blood-glucose level over the span of 120 days, it is not a good marker for T1D control on a day-to-day basis; the occurrence and frequency of dangerous blood-glucose highs (hyperglycemia) and lows (hypoglycemia) are not represented in the A1c. Experts argue that standardization of metrics to measure the success of a person’s T1D control (minimizing high and low blood-sugar exposure) is important, but A1c should not be the sole measure of control.
Since the landmark DCCT study, the HbA1c has been the gold standard metric for diabetes control (3). There is obvious justification for this. The DCCT/EDIC and UKPDS conclusively demonstrated the correlation between HbA1c levels and the development of both microvascular and macrovascular diabetes complications (4-8). HbA1c measures a physiologic process by which the hemoglobin molecule is glycated, which is a surrogate for glycation of other proteins in the body and a driver of diabetes complications (9). Therefore, the HbA1c represents a measurable link between glucose levels and the factors driving complications development.
While the HbA1c will likely remain a key metric and measurement in diabetes management, it is not however a good marker for diabetes control on a day-to-day basis, nor for providing insight into strategies to improve glycemic control. HbA1c reflects the glycation of hemoglobin over the lifespan of erythrocytes—approximately 120 days. This is generally represented or considered as reflecting a mean blood glucose over this period of time. A mean speed of 55 mph over the past three months of commuting will never reflect times when a vehicle is racing at 100 mph and far in excess of the speed limit or is slowed to 10 mph in traffic congestion. Similarly, the clinician receives only the most basic of information from the HbA1c measurement and masks the occurrence and frequency of dangerous highs and lows.
The challenge of defining and prioritizing key diabetes glucose-control metrics was addressed in a workshop with key thought leaders in the field of diabetes, both public and private stakeholders, regulators, and patient representatives. The transition to “big data” is happening in all walks of life and diabetes is no exception, affording a tremendous opportunity to provide data-driven recommendations to patients. Following adoption of a consensus on metrics, tools can and will be developed that present this immense amount of data in ways that can be easily visualized, interpreted, and acted upon. Bergenstal et al. describe one such tool, the Ambulatory Glucose Profile (AGP), that provides a concise and targeted summary to the patient and provider.
The group identified four key metrics that provide much more valuable information in guiding diabetes treatment strategies: time in range (the amount of time a person’s blood glucose is within a healthy range), glycemic variability (exposure to hyperglycemia and hypoglycemia), glycemic exposure (the mean and median of glucose values), and assigned values for blood-glucose ranges signaling hyper- and hypoglycemia.
Once these metrics are agreed upon, tools such as the AGP will provide diabetes clinicians a significantly improved and practical means to guide their patients in targeted strategies to improve diabetes management and glycemic control. The profile presents a modal day view of the data that allows for patterns to be identified quickly and simply, which will allow treatment strategies to be developed during an office visit.
However, we are still not close to achieving our goal of minimizing hyperglycemic and hypoglycemic exposure. The recently published T1D Exchange data demonstrating the elevated A1c levels, severe hypoglycemic events, and overall poor control in many people with diabetes should be a call to action for the diabetes community (10).
We will rapidly move to more advanced tools—soon to systems that automate some insulin delivery (11, 12). Without consensus within the community on the metrics for success, it will prove difficult to optimize and compare new technologies, and their optimal adoption, use, and effectiveness will be blunted, which is an unacceptable outcome.
In addition, a major unaddressed area and a serious unmet medical need is the extended period of “dormant or silent” diabetes—both types 1 and 2—where HbA1c offers little value as a diagnostic. The AGP provides salient metrics with the potential to standardize the early detection and treatment of “pre-diabetes,” thus fostering therapeutic and/or lifestyle interventions that lead to the prevention or delay of onset of overt clinical diabetes.
In order to improve standards of care, we will have to rapidly develop and adopt “composite” metrics for both diagnosis and treatment of individuals with diabetes. To best accomplish our goals, we will need to raise the level of collective education and awareness for accelerated adoption and usage of such metrics—across the entire healthcare spectrum—including patients, physicians, regulators, and providers. It is time to formalize these recommendations and to standardize outcome metrics that will help guide therapeutic development, accelerate regulatory approval, and improve clinical outcomes.
Health-e-Solutions comment: We are all for improving metrics and clinical outcomes. We think the best way to improve clinical outcomes for many people with diabetes is to transform their lifestyles. Our two boys have maintained HbA1c’s of between 4.5 and 5.4 since 2008. Since the DCCT study established 5.6 as the point at which micro- and macrovascular damage begins, they are well below the threshold of tissue damage.
Mapping, monitoring and measuring are a continuous cycle when living with diabetes. You begin with a certain course of treatment in mind, which you mapped out with the help of your medical professional. You monitor your progress and measure it against your goals. Upon evaluation, you may find a new course must be corrected to compensate for successes and challenges. Evaluating progress and results of the Health-e-Solutions lifestyle is essential to #MasterDiabetes in the healthiest way possible. This downloadable e-publication equips you with the key evaluation tools you need, along with some of the research behind them, to determine where you want to go and how to get there. We give you important tools to help you chart your course and stay on track to reach your destination.
- Diabetes Mellitus Interagency Coordinating Committee. Strategic Planning to Enhance Federal Diabetes Programs, August 11, 2008. http://archives.niddk.nih.gov/federal/dmicc/2005/12-12-05/summary.pdf (accessed February 19, 2013).
- Beck RW, Tamborlane WV, Bergenstal RM, Miller KM, Dubose SN, Hall CA; the T1D Exchange Clinic Network: The T1D Exchange Clinic Registry. J Clin Endocrinol Metab 2012;97:4383–4389.
- Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Research Group, Nathan DM, Zinman B, Cleary PA, Backlund JY, Genuth S, Miller R, Orchard TJ: Modern-day clinical course of type 1 diabetes mellitus after 30 years’ duration: the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications and Pittsburgh Epidemiology of Diabetes Complications experience (1983–2005). Arch Intern Med 2009;169:1307–1316.
- The Diabetes Control and Complications Trial Research Group: The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med 1993;329:977–986.
- UK Prospective Diabetes Study (UKPDS) Group: Effect of intensive blood-glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34). Lancet 1998;352:854–865.
- DCCT/EDIC Research Group, de Boer IH, Sun W, Cleary PA, Lachin JM, Molitch ME, Steffes MW, Zinman B: Intensive diabetes therapy and glomerular filtration rate in type 1 diabetes. N Engl J Med 2011;365:2366–2376.
- Writing Team for the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Research Group: Sustained effect of intensive treatment of type 1 diabetes mellitus on development and progression of diabetic nephropathy: the Epidemiology of Diabetes Interventions and Complications (EDIC) study. JAMA 2003;290:2159–2167.
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- Koenig RJ, Peterson CM, Jones RL, Saudek C, Lehrman M, Cerami A: Correlation of glucose regulation and hemoglobin A1c in diabetes mellitus. N Engl J Med 1976;295:417–420.
- Wood JR, Miller KM, Maahs DM, Beck RW, Dimeglio LA, Libman IM, Quinn M, Tamborlane WV, Woerner SE; T1D Exchange Clinic Network: Most youth with type 1 diabetes in the T1D Exchange Clinic Registry do not meet American Diabetes Association or International Society for Pediatric and Adolescent Diabetes clinical guidelines. Diabetes Care 2013 Jan 22 [Epub ahead of print]. doi: 10.2337/dc12-1959.
- Nimri R, Atlas E, Ajzensztejn M, Miller S, Oron T, Phillip M: Feasibility study of automated overnight closed-loop glucose control under MD-Logic artificial pancreas in patients with type 1 diabetes: the DREAM Project. Diabetes Technol Ther 2012;14:728–735.
- Elleri D, Allen JM, Biagioni M, Kumareswaran K, Leelarathna L, Caldwell K, Nodale M, Wilinska ME, Acerini CL, Dunger DB, Hovorka R: Evaluation of a portable ambulatory prototype for automated overnight closed-loop insulin delivery in young people with type 1 diabetes. Pediatr Diabetes 2012;13:449–453.