healthcare related

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

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:
1. Patient self-monitoring of blood glucose (SMBG)
2. HbA1C: the key surrogate for the risk of microvascular complications
• 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. ..
ADVANTAGES
Easy to measure
Relatively cheap
Predictive of vascular
complications
Accepted by payers
and regulatory

HbA1c
The gold
standard
×
LIMITATIONS
Only provides an
approximate
measure of glycemia
Unable to address
GV or hypoglycemia
Unreliable In certain
conditions (renal failure,
Hb abnormalttles, other)

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

7. Diabetes Care 2017;40:994–999
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 HbA1c value

8. 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
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.

9. The need for clinically meaningful measures beyond HbA1c
Diabetes care 2017, 40:1622-1630
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
Time in
range
Hyper-
glycemia
Hypo-
glycemia
DKA PROs
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.

10. Principle of CGM

11. • rtCGM uniformly 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 range combined 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
Diabetes Care 2017; 40: 994–99
Diabetes Care 2015; 38: 1615–21 JAMA 2017; 317: 371–78

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/iCGM
data (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 Technol Ther 2018;20:314–316
Diabetes Care, published online September 17, 2018

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

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
rtCGM group

20. Standardizing Clinically Meaningful Outcome Measures Beyond HbA1c
Diabetes Care 2017;40:1622-30
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

21. Different ECG Devices-Same Output

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

24. CGM Metrics for visualization, analysis, and documentation
Diabetes care 2017,40:1633-40
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

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 and
reduced severe hypoglycemia
Lancet Diabetes Endocrinol 2016; 4: 891-902

30. HbA1c compared with time in range
HbA1c testing Time in range outcome
Evaluates single HbA1c levels Evaluates continuous glucose levels
Compares HbAlc levels
3 months apart
May compare fluctuations for any given
amount of time
Does not capture hypoglycemic or
hyperglycemic levels occurring In
the same day
Captures all glucose levels for the given
time frame and Identifies time within a
safe range
Less likely to capture Impact of
acute Interventions
Likely to capture impact of
acute Interventions
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
#1
Unexpected BG
numbers
#2
Dosing insulin
#3
Hypoglycemia
#4
A1c
#5
Time in range
#1
A1c
#2
Nondiabetes health
issues
#3
Dosing insulin
#4
Unexpected BG
numbers
#5
Time in range
#1
A1c
#2
Nondiabetes health
issues
#3
Unexpected BG
numbers
#4
Symptoms of
complications
#5
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 Endocrinol 2017, 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 Technol Ther 2014;16:303–309
Diabetes Technol Ther 2012;14:1008–1012 Diabetes Care2017;40:832–838

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 vs Gla-100
• Continuous glucose monitoring confirms if PK/PD differences translate to clinically relevant differences
Diabetes care 2017;40:554-60
Gra·300 vs Gra-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

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 2018 32(7):682-687 Diabetes Care 2015 38(1)

43. Glucose fluctuations have been associated with
diabetes-related complications
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
Clin chem 2014;60:409-18
Adjusted association for baseline l ,5-AG with prevalent retinopathy
(ORs) and Incident CKD (HRs) in the overall population

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 insulins with 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
BETTER
OUTCOMES
FOR PATIENTS
Avoid hypoglycemia