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Current and Future Challenges in Diabetes Prevention, Diagnosis

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'So, Mrs. Smith, it looks like you do have diabetes. ... HbA1c: useful for research, risk prediction, target of therapy. Well standardized ... – PowerPoint PPT presentation

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Title: Current and Future Challenges in Diabetes Prevention, Diagnosis


1
Use of the Estimated Average Glucose (eAG) in
Patient Care
2
A Typical Patient Encounter
  • So, Mrs. Smith, it looks like you do have
    diabetes. Your repeat fasting blood sugar was
    178, and as you recall the first one was 187.
    Over 126 is diabetes. Also, your hemoglobin A1c
    was way too high at 8.6. Normal is less than
    6. We need to get it below 7.

3
A Typical Patient Encounter
  • Whats a hemoglobin Awhatever you said? I
    remember my hemoglobin was low when I was
    pregnant. What were those other numbers? What
    do you mean, 7...of what?

4
G
G
G
G
G
G
G
G
G
G
?
__
G

G
G
G
G
5
Uh
???
6
Its Not Just Confusing forNewly Diagnosed
Patients
  • High levels of testing of HbA1c for patients with
    known diabetes (gt 90).
  • Of patients with test in past 6 months
  • 66 did not know result
  • 25 accurately reported within 1 range
  • (lt 7, 7-8, 8-9)
  • 9 inaccurately reported within 1 range

Heisler, Diabetes Care 28816,2005
7
The Clinical Dilemma
  • HbA1c useful for research, risk prediction,
    target of therapy
  • Well standardized
  • HOWEVER, difficult to explain to patients
  • Concept of is not intuitive
  • Glucose more familiar to patients from
    self-monitoring or from laboratory glucose results

8
The Concept of Average Glucose
  • We tell patients the HbA1c reflects their
    average glucose over 2-3 months
  • But do we know this for sure?

9

10
The A1C-Derived Average Glucose (ADAG) Study
  • International study designed to
  • Carefully look at relationship between HbA1c and
    average glucose
  • Determine the mathematical relationship between
    the two for reliable conversion
  • Establish that the relationship is valid across
  • - Diabetes types
  • - A wide range of HbA1c levels and age
  • - Different races/ethnicities

Nathan et al, Diabetes Care 311473, 2008
11
ADAG Study Centers
  • Cameroon
  • Denmark
  • Italy
  • The Netherlands
  • United States
  • Boston
  • New York
  • San Antonio
  • Seattle
  • India (site dropped due to specimen handling
    issues)

12
Participants in ADAG
  • Goal was to recruit people with
  • Type 1 diabetes
  • Type 2 diabetes
  • No diabetes
  • With a range of
  • Ethnicity/race
  • HbA1c levels
  • Excluded those with conditions that would
    interfere with measurement/interpretation of
    HbA1c or glucose

13
Measures of Glycemia in ADAG Study
  • CGM (calibrated by 8-point glucose profiles with
    Hemocue meter) for at least 48 hours at baseline
    and every month for 3 months
  • 7-point glucose profiles for 3 days per week with
    One Touch Ultra meter
  • HbA1c at baseline and monthly X 3 months with
    DCCT-aligned assay in a central laboratory
  • Four measures of HbA1c to assure stable control,
    but only final value used for correlation with
    prior 3 months glucose readings

14
ADAG Study Flow
Total Enrolled 661 Eliminated from analysis 154
(23) - Dropped out or excluded 91 (14)
during study - Inadequate CGM 11 (2)
- Inadequate HbA1c samples 52 (8)
15
Baseline Characteristics of ADAG Participants
16
ADAG Study Distribution of Baseline HbA1c
44
Number of subjects
38
18
Baseline HbA1c ()
17
ADAG Study Glucose Monitoring
  • CGM mean of 2,400 measurements per
    participant
  • LifeScan meter mean of 300 measurements per
    participant
  • Mean of 25 measurements per week
  • Goal was a minimum of 21 tests per week
  • Total 2,700 measurements/participant during 12
    weeks

18
ADAG Study Analyses
  • CGM results corrected upward by 5 to be
    consistent with BG
  • Each glucose measure weighted in proportion to
    the inverse of total number of measurements on
    that day (each day had equal weight)
  • Arithmetic mean glucose calculated for each
    participant
  • Linear regression model used to estimate
    relationship between average glucose and the
    3-month HbA1c

19
ADAG Study Study Success
90 of values fell within /- 15
HbA1c ()
20
ADAG Study Correlation of AG With HbA1c
AG (mg/dl) 28.7 x HbA1c 46.7 R2 0.84
P lt 0.0001
AG (mg/dl)
HbA1c ()
21
ADAG Study Correlation of AG with HbA1c CGM
data vs. Meter
No difference in relationship (P0.18) whether
LifeScan or CGMS data used
HbA1c ()
22
ADAG Study Other Factors Examined
  • Does the HbA1c-Average Glucose relationship
    differ by
  • - Type 1 or type 2 diabetes NO
  • - Diabetes or no diabetes NO
  • - Amount of glucose variability NO
  • - Gender NO
  • - Age NO
  • - Ethnicity/Race NO
  • (but trend toward higher HbA1c per AG in
    African and African-American participants vs.
    whites, P0.07)
  • - Smoking NO

23
ADAG Study Excluded Known Sources of Inaccuracy
of HbA1c
  • Hemoglobinopathy
  • Anemia
  • Pregnancy
  • Hepatic or renal disease
  • Etc.

24
ADAG Study Conclusion HbA1c Correlates Highly
With AG
450
400
AG (mg/dl) 28.7 x HbA1c 46.7
350
300
AG (mg/dl)
250
200
150
100
50
3
4
5
6
7
8
9
10
11
12
13
Measured HbA1c ()
25
Implications
  • Tight correlation between HbA1c and AG allows us
    to translate HbA1c into an estimated Average
    Glucose (eAG)
  • eAG will apply to the majority of patients with
    diabetes
  • Barring traditional conditions interfering with
    the assay or the relationship between glycemia
    and HbA1c

26
ADAG Study Translation of HbA1c into eAG
eAG HbA1c () (mg/dl) (mmol/l)_ 5
97 5.4 6 126 7.0 7 154
8.6 8 183 10.2 9 212 11.8 10
240 13.4
27
Note that the numbers are different
ADAG DCCT HbA1c () (mg/dl)___(mg/dl)______
6 126 135 7 154 170 8 183
205 9 212 240 10 240 275
28
Consensus Statement FCC, EASD, IDF, ADA Sept 2007)
  • HbA1c assay to be standardized worldwide using
    the new IFCC standard and expressed as
  • as currently used (DCCT values)
  • IFCC units in mmol HBA1c/mol HbA
  • eAG in mmol/l or mg/dL (if ADAG study meets its
    data acceptability goals)
  • This paved the way for reporting both HbA1c and
    EAG on lab reports

Diabetes Care and Diabetologia, 2007
29
What Wont ChangeAnd Whats New
  • To a clinician, there is no change in the HbA1c
    assay
  • To clinical chemists, there is a new IFCC
    standard in the background
  • We have the potential for a valuable educational
    tool for patients

30
A Typical Patient Encounter
  • So, Mrs. Smith, it looks like you do have
    diabetes. Your average blood sugar is around 200.
    When people dont have diabetes, this number is
    below 125. We need to work with you to try to
    get this number, the average glucose, down below
    150 over the next few months with some weight
    loss, exercise, and a medication. Lets talk some
    more about what you can do

31
A Typical Patient Encounter
Wow, Im not happy to hear thatI know that
diabetes can do some bad things. Tell me what I
can do to get my average glucose down.
32
What is ADA Doing to Promote Use of eAG in
Patient Care?
  • Health care provider education
  • ADA Scientific Sessions, June 08
  • American Association of Clinical Chemists, August
    08
  • AADE Annual Meeting, August 08
  • eAG calculators (handheld and on
    professional.diabetes.org)
  • Patient education
  • Website
  • Diabetes Forecast magazine, books
  • Pamphlets and brochures
  • ADA will include term average glucose in all
    consumer pieces

33
What Can Clinicians and Educators Do?
  • Choose which termA1C or Average Glucoseto use
    with each patient (some may already be used to
    A1C)
  • In verbal communications, no need to say
    estimated
  • We want to keep the A in A,B,Cs
  • Use updated table, calculator on
    www.diabetes.org, or other tools to convert A1C
    to average glucose
  • Lobby your lab to report both numbers

34
What Can Clinical Chemists Do?
  • Even with tools, most clinicians will not take
    the time to calculate conversions
  • Reporting both HbA1c (DCCT-aligned) AND eAG on
    lab reports will do the most to promote wide use
    of the term
  • Professional and patient education may drive
    demand
  • Conversion is a simple regression equation

35
Average Glucose Blood pressure Cholesterol
to help make the A understandable!
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