Continuous glucose monitoring (CGM) outcomes provide meaningful metrics for clinical trials and diabetes care, but the benefits can’t be demonstrated without a standard set of definitions, according to a panel of experts who spoke at a Friday symposium.
The researchers outlined three published and three forthcoming CGM metric statements, and called for combining those into one international consensus during the session Reaching an International Consensus on Standardizing Continuous Glucose Monitoring (CGM) Outcomes—Aligning Clinicians, Researchers, Patients, and Regulators. A unified set of definitions would aid in the development of new drugs and devices, the researchers said.
Key metrics derived from CGM data include time in range of glucose levels, time above range, time below range, and glucose variability, which may impact both hyperglycemia and hypoglycemia and may have other detrimental effects.
“CGM has the potential to be a critical tool in clinical trials to evaluate and compare new medications and new technologies to see which is more effective at obtaining more control and minimizing hypoglycemia and variability,” said Richard M. Bergenstal, MD, Executive Director of the International Diabetes Center at Park Nicollet. “But with no standard definition, every trial might use a different definition of what’s high and what’s low, so we can’t easily compare the data. We need to get everyone to agree.”
The researchers reviewed three published CGM consensus statements: The International Hypoglycaemia Study: A Joint Position Statement of ADA and EASD; Outcome Measures for Artificial Pancreas Clinical Trials: A Consensus Report; and results from the Helmsley/IDC Standardized Glucose Reporting Expert Working Group.
They also highlighted the findings of three soon-to-be published CGM consensus statements: Improving the Clinical Value and Utility of CGM Systems: Issues and Recommendations, ADA-EASD Diabetes Technology Working Group; Priority Outcome Measures for Type 1 Diabetes: Consensus Statement of JDRF, Helmsley Charitable Trust, AACE, Endocrine Society, PES, AADE, T1D Exchange and ADA; and the International Consensus Statement on CGM Outcomes: ATTD.
A key point repeated often during the symposium is the fact that there’s only a slight difference in the suggested values for many CGM metrics. For example, in the six CGM consensus statements noted in the session, hypoglycemia was defined as: 70 mg/dL, <70 mg/dL, <60 mg/dL, <55 mg/dL, <54 mg/dL, and <50 mg/dL.
Simon Heller, FRCP, MD, Professor of Clinical Diabetes at the University of Sheffield, England, argued that there needs to be three standard glucose levels to manage hypoglycemia.
“If you’re going to have glucose levels that are relevant to hypoglycemia, you can’t have one or two. We have argued for three,” he said. “You don’t want a patient to go down as low as 54 mg/dL. By that time, they’re already in trouble. People need to be aware that hypoglycemia has consequences that aren’t captured by current classifications and in research studies and in clinical trials.”
Thomas Danne, MD, PhD, Director of the Department of General Pediatrics and Endocrinology/Diabetology at Kinderkrankenhaus auf der Bult in Hannover, Germany, outlined the levels he, and other experts in the room, believed should be the “standard” metrics.
Dr. Danne said time out of range has two components: moderate and serious hypoglycemia. For reasons of conformity, the terms ‘alert hypoglycemia’ and ‘serious hypoglycemia’ are recommended to be used analogously for CGM and self-monitoring blood glucose (SMBG) threshold ranges, he said.
Dr. Danne added that a key measure of glycemic variability is the coefficient of variation (CV), which is independent of mean glucose concentration. Stable glucose levels are defined as a CV 50 percent, and intermediate stability as CV between 33 and 50 percent, he said.
“A composite goal of flash glucose monitoring or CGM, reported in a standardized way and in conjunction with an A1C value, could establish with more confidence whether or not a particular insulin formulation, new technology for insulin delivery, or an innovative patient-centered approach to care was an important factor in helping individuals with diabetes reach optimal glycemic control,” Dr. Danne said.
Aaron J. Kowalski, PhD, Chief Mission Officer for the JDRF, said the diabetes community needs to recognize that although important, A1C has limitations. Dr. Kowalski has been working with the T1D Outcomes Program, a community to develop better ways to define clinically meaningful type 1 diabetes outcomes beyond A1C.
Dr. Bergenstal agreed with Dr. Kowalski’s assessment of A1C.
“A1C doesn’t tell you where you were high or where you were low, or how you should adjust your medication,” Dr. Bergenstal said. “If you’re doing it for research, it tells you your risk for complications, but it doesn’t tell you if you have more or less hypoglycemia. CGM adds important information to the A1C. Instead of getting in a fight with the A1C, CGM adds value and gives you the whole picture, or tells you the patient’s story.”
Unlike blood glucose meters, CGM devices have the ability to measure 96 to 288 blood sugars every day and allow patients to monitor their glucose “continuously” to help avoid reaching hypoglycemia, Dr. Danne said.
Other CGM hurdles include technology software and data visualization. Companies that make CGM devices have proprietary software that makes it difficult to compare data across systems or companies, Dr. Heller said.
From a clinician’s perspective, it’s difficult to look at data from different devices that use different target ranges and standards for hyperglycemia and hypoglycemia, agreed Anne Peters, MD, Director of the University of Southern California Clinical Diabetes Program.
“It increases the complexity of analysis and can lead to errors in interpretation and dose adjustments,” Dr. Peters said. “A common set of standards would lead to an easier way to interpret research trial results, as well as data viewed in a clinical setting.”
Drs. Peters and Heller urged industry and developers to create one default reporting system or way to visualize CGM profiles and patterns.
If the diabetes community—clinicians, researchers, patients, developers, and regulators—can agree on a consensus for CGM metrics and visualization, it will help everyone with the end goal: Helping people with diabetes self-manage their condition more effectively, Dr. Heller said.
“We’re beginning to have technologies that can [help with that goal], but the trouble is they’re expensive,” he said. “Governments and health insurance companies are unwilling to pay this money because they don’t see the potential benefit. We’ve got to do something about that. Technology and people’s abilities to use them effectively have to be a major focus for assisting people to live with this incredibly burdensome condition. If people can get it right, people with diabetes can live with both improved quality of life and a normal life expectancy.”