Use of eAG in Patient Care Powerpoint presentation

www.diabetes.org 1-800-DIABETES

Use of the Estimated Average Glucose (eAG) in Patient Care


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%.”


A Typical Patient Encounter “What’s a hemoglobin A…

whatever you said? I remember my hemoglobin was low when I was pregnant. What were those other numbers? What do you mean, 7%...of what?”


G

G

GG

G

GGG

G

= __%GGG

GGG


Uh…

???


It’s Not Just Confusing forNewly Diagnosed Patients

• High levels of testing of HbA1c for patients with known diabetes (> 90%).

• Of patients with test in past 6 months:– 66% did not know result– 25% accurately reported within 1% range

(< 7%, 7-8%, 8-9%)– 9% inaccurately reported within 1% range

Heisler, Diabetes Care 28:816,2005


The Clinical Dilemma• HbA1c: useful for research, risk

prediction, target of therapy• Well standardized• HOWEVER, difficult to explain to patients • Concept of % is not intuitiveConcept of % is not intuitive• Glucose more familiar to patients from Glucose more familiar to patients from

self-monitoring or from laboratory glucose self-monitoring or from laboratory glucose resultsresults


• We tell patients the HbA1c reflects their We tell patients the HbA1c reflects their “average glucose over 2-3 months”“average glucose over 2-3 months”

• But: do we know this for sure?But: do we know this for sure?

The Concept of Average GlucoseThe Concept of Average Glucose


Study Year Cohort Study period

(weeks)Number of

glucose tests per patient

per 1-3 months

Svendsen 1982 15 T1DM 5 200-300

Nathan 1984 21 T1DM 8 200-300

DCCT 2002 1439 T1DM 12 7

Hempe 2002 128 T1DM 4 80

Murata

Nathan

2004

2007

182 T2DM

22 T1DM3 Normals

8

12

180

24,000(CGMS)


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 31:1473, 2008


ADAG Study Centers

• Cameroon• Denmark• Italy• The Netherlands

• United States– Boston– New York– San Antonio– Seattle

• India (site dropped due to specimen handling issues)


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


Measures of Glycemia in ADAG Study• CGM (calibrated by 8-point glucose profiles with CGM (calibrated by 8-point glucose profiles with

Hemocue meter) for at least 48 hours at baseline Hemocue meter) for at least 48 hours at baseline and every month for 3 monthsand every month for 3 months

• 7-point glucose profiles for 3 days per week with 7-point glucose profiles for 3 days per week with One Touch Ultra meterOne Touch Ultra meter

• HbA1c at baseline and monthly X 3 months with HbA1c at baseline and monthly X 3 months with DCCT-aligned assayDCCT-aligned assay in a central laboratory in a central laboratory

• Four measures of HbA1c to assure stable control, Four measures of HbA1c to assure stable control, but only final value used for correlation with prior but only final value used for correlation with prior 3 months’ glucose readings3 months’ glucose readings


Total EnrolledTotal Enrolled 661661

Eliminated from analysisEliminated from analysis 154 (23%)154 (23%)

- Dropped out or excluded- Dropped out or excluded 91 (14%) 91 (14%) during studyduring study

- Inadequate CGM- Inadequate CGM 11 (2%)11 (2%)

- Inadequate HbA1c samples- Inadequate HbA1c samples 52 (8%)52 (8%)

ADAG Study FlowADAG Study Flow


Type 1 Type 2 Non-DM Total

Number 268 159 80 507

Age 43 + 13 56 + 9 40 + 14 46 + 14

Gender (% F) 52%52% 50%50% 69%69% 54%54%

Race/Ethnicity

White 93% 73% 71% 83%

African/Af-Am 2% (5) 13% (21) 15% (12) 8% (38)

Hispanic 6% (15) 8% (12) 15% (12) 8% (39)

TreatmentPump / ≥3 inject/day 47% / 53%

Diet only/ 10%

Oral agent only 52%

Insulin only 19%

Insulin & oral 19%

Baseline Characteristics of ADAGBaseline Characteristics of ADAG ParticipantsParticipants


050

100150200250300350400

4-6.5 6.6-8.5 >8.5

Baseline HbA1c (%)Baseline HbA1c (%)

NumberNumber ofof

subjectssubjects

44%

18%

Normal

Diabetic

38%

ADAG Study: Distribution of BaselineADAG Study: Distribution of Baseline HbA1cHbA1c


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


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


ADAG Study: Study SuccessADAG Study: Study Success

90% of values fell within +/- 15%90% of values fell within +/- 15%

0

2

4

6

8

10

12

14

16

18

Cal

c. A

G

(mm

ol/L

)

90% ofcohort valuesfall in this range

HbA1c (%)


ADAG Study: Correlation of AG With HbA1c

AG

(mg/

dl)

HbA1c (%)

AG (mg/dl) = 28.7 x HbA1c – 46.7 R2 = 0.84 P < 0.0001


ADAG Study: Correlation of AG with HbA1c: CGM data vs. Meter

CGM calc. AG = 1.649x - 2.645R2 = 0.768

0

24

6

8

10

12

14

16

18

3 4 5 6 7 8 9 10 11 12 13

Cal

c. A

G (m

mol

/L)

HbA1c (%)HbA1c (%)

No difference inrelationship (P=0.18) whether LifeScan orCGMS data used


ADAG Study: Other Factors ExaminedADAG Study: Other Factors Examined• Does the HbA1c-Average Glucose relationship differ by:Does the HbA1c-Average Glucose relationship differ by: - - Type 1 or type 2 diabetes Type 1 or type 2 diabetes NO NO

- Diabetes or no diabetes - Diabetes or no diabetes NONO- Amount of glucose variability - Amount of glucose variability NONO

- Gender - Gender NONO - - Age Age NONO- Ethnicity/Race - Ethnicity/Race NONO (but trend toward higher HbA1c per AG in African (but trend toward higher HbA1c per AG in African and and African-American participants vs. whites, P=0.07)African-American participants vs. whites, P=0.07)

- - Smoking Smoking NONO


ADAG Study Excluded Known Sources of “Inaccuracy” of HbA1c

• Hemoglobinopathy• Anemia• Pregnancy• Hepatic or renal disease• Etc.


ADAG Study Conclusion: ADAG Study Conclusion: HbA1c Correlates Highly With AGHbA1c Correlates Highly With AG

Measured HbA1c (%)

AG (mg/dl) = 28.7 x HbA1c – 46.7

50100150

200250

300

350400450

3 4 5 6 7 8 9 10 11 12 13

AG

(mg/

dl)


• Tight correlation between HbA1c and AG Tight correlation between HbA1c and AG allows us to translate HbA1c into an allows us to translate HbA1c into an estimated Average Glucose (eAG)estimated Average Glucose (eAG)

• eAG will apply to the majority of patients eAG will apply to the majority of patients with diabeteswith diabetes– Barring “traditional” conditions interfering Barring “traditional” conditions interfering

with the assay or the relationship between with the assay or the relationship between glycemia and HbA1cglycemia and HbA1c

ImplicationsImplications


ADAG Study: “Translation” of HbA1c into eAG

eAG HbA1c (%) (mg/dl) (mmol/l)_

5 97 5.46 126 7.07 154 8.68 183 10.29 212 11.810 240 13.4


Note that the numbers are different

ADAG DCCTHbA1c (%) (mg/dl)___(mg/dl)______

6 126 1357 154 1708 183 2059 212 24010 240 275


Consensus Statement FCC, EASD, IDF,Consensus Statement FCC, EASD, IDF, ADA Sept 2007)ADA Sept 2007)

Diabetes Care and Diabetologia, 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


What Won’t Change…And What’s NewWhat Won’t Change…And What’s 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


A Typical Patient Encounter “So, Mrs. Smith, it looks like you do

have diabetes. Your average blood sugar is around 200. When people don’t 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. Let’s talk some more about what you can do…”


“Wow, I’m not happy to hearthat…I know that diabetes can do some bad things. Tellme what I can do to get myaverage glucose down.”

A Typical Patient Encounter


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


What Can Clinicians and Educators Do?

• Choose which term—A1C or Average Glucose—to 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


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


Average GlucoseBlood pressureCholesterol

to help make the “A” understandable!

Documents

Use of eAG in Patient Care Powerpoint presentation