Mohammad E. Khamseh Institute of Endocrinology and Metabolism Iran University of Medical Sciences

1. 12th International Congress of Endocrine Disorders Beyond HbA1c Glycemic Metrics Mohammad E. Khamseh Institute of Endocrinology and Metabolism Iran University of Medical Sciences 15th November 2018 Tehran, Iran

2. Objectives • Understand the role of HbA1c as a measure of glycemic control and its limitations • Explore additional glycemic metrics, with a focus on time in range, glucose variability (GV) and its correlation with clinical outcomes • Review recent evidence of improved GV with some glucose-lowering agents • Consider how assessment of GV and the use of CGM can support management decisions and improve patient outcomes

3. Assessment of Glycemic Control • Primary techniques available to assess effectiveness of glycemic control: • Patient self-monitoring of blood glucose (SMBG) • HbA1C: the key surrogate for the risk of microvascularcomplications • CGM may have an important role assessing the effectiveness and safety of treatment in selected patients. American Diabetes Association Standards of Medical Care in Diabetes. Glycemic targets. Diabetes Care 2018

4. History of glucose monitoring The development of reliable CGM may be turning point in the management of diabetes

5. HbA1c is the mainstay of blood glucose measurement, however. .. HbA1c The gold standard × 

6. Range of mean glucose concentrations for observed HbA1c levels in pooled data Diabetes Care 2017;40:994–999

7. The shaded area represents the 95% prediction interval (analogous to an individual CI) for a patient’s mean glucose concentration for a measured HbA1c level, demonstrating the wide range of mean glucose concentration values that are possible for any HbA1cvalue Diabetes Care 2017;40:994–999

8. CALL TO ACTION Current A1c-focused regulatory decisions do not accurately reflect the recent advances in diabetes technology, namely CGM systems, and cannot capture the daily reality of living with diabetes. As riddle et al. recently declared, “periodically, a new idea, method, or tool leads to a turning point in the management of diabetes. We believe such a moment is now upon us, brought by development of reliable devices for continuous glucose monitoring” (6). Thus, regulatory bodies should acknowledge therapies that improve time in range, glycemic variability, and quality of life, which is impossible without incorporating these agreed upon core glycemic metrics into regulatory decisions. To address identified clinical gaps and make progress on next steps, the diabetes community needs to continue to engage regulatory bodies in discussions to agree on how, when, and where these metrics should be used for clinical trial design and risk-benefit decisions. The diabetes community has reached consensus and, in doing so, aims to empower regulatory bodies to implement outcomes beyond A1c. Need for Regulatory Change to Incorporate Beyond A1C Glycemic Metrics Beyond A1c Writing Group Diabetes Care 2018;41:e92-e94|http://doi.org/10.2337//dci18-0010

9. The need for clinically meaningful measures beyond HbA1c Time in range Standardizing Clinically Meaningful Outcome Measures Beyond HbA1c for Type 1 Diabetes: A Consensus Report of the American Association of Clinical Endocrinologists, the American Association of Diabetes Educators, The American Diabetes Association, the Endocrine Society, JDRF International, The Leona M. and Harry B. Helmsley Charitable Trust, the Pediatric Endocrine Society, and the T1D Exchange Hypo-glycemia Hyper- glycemia CONCLUSIONS The Steering Committee recommends use of the defined clinically meaningful outcomes beyond HbA1c in the research, development,and evaluation of type 1 diabetes therapies. DKA PROs Diabetes care 2017, 40:1622-1630

10. Principle of CGM

11. rtCGMuniformly tracks the glucose concentrations in the body’s interstitial fluid, providing near real-time glucose data. Warn users if glucose is trending toward hypoglycemia or hyperglycemia • iCGM uses similar methodology to show continuous glucose measurements retrospectively at the time of checking Diabetes Care 2017;40:1631–1640

12. The CGM metric of time in target rangecombined with time in hypoglycaemia can provide a more personalised approach to diabetes management. • Viewing rtCGM data can help individuals learn how dramatically glucose can rise after certain meals or change with stress (usually rising) or exercise (usually falling) • CGM might be the best example of diabetes precision medicine JAMA 2017; 317: 371–78 Diabetes Care 2017; 40: 994–99 Diabetes Care 2015; 38: 1615–21

13. 10–14 days of CGM data provide a good estimate of CGM metrics for a 3-month period • An estimated HbA1c (eA1C) can be calculated if adequate rtCGM/iCGMdata (70% or 10 days of the 14 days of CGM data) are available • A laboratory-measured A1C of 8.0% could be associated with a CGM-measured mean glucose concentration as low as 155 mg/dl (for which the eA1C from mean glucose would be 7.0%) or as high as 218 mg/dl (for which the eA1C from mean glucose would be 8.5%) Diabetes Care, published online September 17, 2018 Diabetes TechnolTher2018;20:314–316

14. Glucose management indicator (GMI) • The leading candidates to replace eA1C • GMI(%)=3.31+0.02392mean glucose in mg/dL • Combining data from four randomized trials using the Dexcom G4 sensor

15. GMI calculated for various CGM-derived mean glucose concentrations Diabetes Care, published online September 17, 2018

16. If the target A1C is 7.0% but the GMI is always lower (6.6%), it would be advisable to ensure that the time spent in hypoglycemia is not excessive. Setting a slightly higher A1C target (7.3%) may be advisable to minimize the risk of hypoglycemia.(Longer RBC life span (slower RBC turnover rate) than average or a higher RBC glycationrate than average) • If the target A1C is 7.5% and the GMI is always higher (7.9%), it might be safe to set the A1C target slightly lower, such as at 7.2%, in order to minimize excessive hyperglycemia. • The difference in laboratory A1C and GMI remains relatively stable for each individual over time. Diabetes Care, published online September 17, 2018

17. Difference between GMI and laboratory-measured A1C (N = 528) Diabetes Care, published online September 17, 2018

18. Lancet, Vol 391, April 7, 2018

19. Cumulative distribution of hypoglycaemic events per 28 days at baseline and follow-up in the control group Cumulative distribution of hypoglycaemic events per 28 days at baseline and follow-up in the rtCGMgroup

20. Standardizing Clinically Meaningful Outcome Measures Beyond HbA1c Standardizing Clinically Meaningful Outcome Measures Beyond HbA1c for Type 1 Diabetes: A Consensus Report of the American Association of Clinical Endocrinologists, the American Association of Diabetes Educators, The American Diabetes Association, the Endocrine Society, JDRF International, The Leona M. and Harry B. Helmsley Charitable Trust, the Pediatric Endocrine Society, and the T1D Exchange Diabetes Care 2017;40:1622-30

21. Different ECG Devices-Same Output

23. HbA1c alone may misrepresent mean blood glucose levels Four T1DM patients with same lab HbA1c have different ambulatory glucose profiles and estimated HbA1c values Beck RW, et al. Diabetes care 2017;40:994-9

24. CGM Metrics for visualization, analysis, and documentation Consensus statement established 14 key CGM metrics including: Mean glucose Percentage of time in <70 and <54 mg/dL hypoglycemia range Percentage of time-in-target range: 70-180 mg/dL Glycemic variability Diabetes care 2017,40:1633-40

25. From 7-point SMBG to Ambulatory Glucose Profile There are various ways beyond HbA1c that blood glucose data can be used to Inform diabetes management decision making and during clinical trials

26. Time-in-target range is becoming the new standard for providers and patients

27. Time in Ranges

28. Correlation of time in range and HbA1c http://www.agpreport.org/agp/agpreports#SMBG_AGP

29. Use of CGM is associated with increased time in range andreduced severe hypoglycemia Lancet Diabetes Endocrinol 2016; 4: 891-902

30. HbA1c compared with time in range HbA1c testing Time in range outcome Diabetes care 2017,40:1622-1630

31. Association of time in range from CGM with diabetic retinopathy in T20M Lu J et al, Diabetes care 2018, Epub ahead of print

32. Patients rank time in range as a leading factor having "A big impact" on daily life T1D (n=1 ,106) T2D on Insulin (n=1 ,141) T2D no Insulin (n=1 ,266) Time in range Symptoms of complications Unexpected BG numbers Dosing insulin Unexpected BG numbers Hypoglycemia Unexpected BG numbers Time in range Nondiabetes health issues Time in range A1c A1c Nondiabetes health issues Dosing insulin A1c #1 #2 #3 #4 #5 #1 #5 #2 #4 #3 #1 #4 #2 #5 #3 Htpp://diatribe.org

33. Going beyond HbA1c: Glucose variability Patients with diabetes face optimization challenges Achieving glycemic control while avoiding hypoglycemia, which may be associated With Intensive HbA1c lowering 1 Safely optimizing control In the context of lowering glucose variability (GV) (fluctuations In glucose levels that occur from hyperglycemic peaks and hypoglycemic troughs )2 1. Nat Rev Endocrinol2017, 11:425-36 2. Diabetes Care 2015, 38:1610-14

34. Degree of glycemic variability potentially associated with hypoglycemia 15-day glucose traces of two patients with diabetes who had an identical HbA1c of 8.0% Both patients have similar average glucose levels Patient A had visibly higher glucose fluctuations. which resulted in: 7 episodes of moderate hypoglycemia (≤50 mg/dl) 8 episodes of moderate hyperglycemia (≥350 mg/dl) Diabetes care 2016;39:502-10

35. Hypoglycemia quantification • The percentage of CGM values that are below a given threshold (<70 mg/dL[3.9 mmol/L] or <54 mg/dL[3.0 mmol/L]) or the number of minutes or hours below these thresholds. • The number of hypoglycemic events that occur over the given CGM reporting period • Readings below the threshold for at least 15 min is considered an event Diabetes Care 2017;40:1631–1640

36. Someone who has an A1C of 6.8% and who spends 10% of the day in hypoglycemia would benefit from a care plan different than someone who has an A1C of 6.8% and who spends 1% of the day in hypoglycemia. Diabetes Care, published online September 17, 2018

37. Measuring glucose variability Diabetes care 2016;39:502-10

38. Glycemic variability • Characterized by the amplitude, frequency, and duration of the fluctuation • Both the amplitude and the timing of blood glucose fluctuations contribute to the risks for hypoglycemia and hyperglycemia • A consistent predictor of hypoglycemia • CV (SD divided by the mean): advantage of being a metric relative to the mean • Stable glucose levels are defined as a CV <36% Diabetes TechnolTher2012;14:1008–1012 Diabetes Care2017;40:832–838 Diabetes TechnolTher2014;16:303–309

39. Factors affecting glucose variability Many factors affect patient glycemic stability, including: Lifestyle Diet Comorbidities Diabetes treatment

40. Less glycemic variability and reduced nocturnal hypoglycemia with Gla-300 vsGla-100 • Continuous glucose monitoring confirms if PK/PD differences translate to clinically relevant differences Gra·300 vsGra-100: Improved glycemic control, with less fluctuation Reduced nocturnal confirmed or severe hypoglycemia: 4.0 vs. 9.0 events/pt-year rate ratio 0.45; 95% cl 0.24-0.82 Diabetes care 2017;40:554-60

41. Impact of sotagliflozin on glycemic variability in adults with T1DM in Tandem 1 & 2 CGM substudy pooled analysis Danne I et al, ADA 2018, poster

42. Glucose variability and complications In the short-term, GV is associated with a range of complications Hypoglycemia ICU mortality Cognitive impairment Reduced QoL Negative mood Critical Care Med, 2010, 38(3):838-42 J Diabetes Comp 201832(7):682-687 Diabetes Care 2015 38(1)

43. Glucose fluctuations have been associated withdiabetes-related complications Adjusted associationfor baseline l ,5-AG with prevalent retinopathy (ORs) and Incident CKD (HRs) in the overall population In the Atherosclerosis Risk in Communities (ARIC) Study, low levels of 1,5-anhydroglucitol (l,5-AG), a marker associated with GV, were associated with an increased risk of retinopathy and incident chronic kidney disease Clinchem 2014;60:409-18

44. Take home messages • HbA1c Is the current gold standard for assessing glycemic control. • We need to: Standardize the data, view the data, use the data • The CGM metric provide a more personalised approach to diabetes management. • CGM detects within-day and day-to-day GV, which may enhance patient self management of diabetes • Glucose variability: • May be linked to the pathogenesis of diabetes complications • Could impact patient diabetes management and quality QOL • Newer glucose-lowering agents (SGLT Inhibitors or GLP-1RA) and basal insulinswith smoother pharmacodynamic profiles can Impact on glucose variability. • Randomized trials are needed that examine the relationship between glucose variability and hard endpoints, such as retinopathy, nephropathy or CV outcomes Improve time in range Limit glucose variability BETTER OUTCOMES FOR PATIENTS Avoid hypoglycemia