Tom A. Elasy, M.D., M.P.H. Vanderbilt University February, 2012.

Diabetes Care: So clear yet so hard

Tom A. Elasy, M.D., M.P.H.Vanderbilt University

February, 2012

So Clear

Scalability◦ People◦ Intervention◦ Context

Sustainability◦ Theories◦ Interventions: induction vs. maintenance

Monitoring Goal setting

Yet so hard

Yarnall KS, et al. Am J Public Health 2003;93:635-641

So hard

A line of inquiry◦ “Relapse” in glucose control◦ Causes of Relapse◦ A Taxonomy of Interventions◦ Results of a RCT to prevent Relapse

Implications

Outline

64 y.o. woman presents to establish primary care – referred by NP in endocrine clinic. “I’m not doin’ so good. My life has been chaotic lately.”

PMHx: DM dx’d 1992 – started insulin 2yrs prior to presentation

HTN Depression –pharmacotherapy for

3yrs OA – primarily of Left Knee

Case Presentation

Medication: Lisinopril, HCTZ, Metformin, Glipizide, Basal/Bolus(fixed) insulin, ASA, Citalopram, Simvastatin, occasional Tylenol #3

SHx: Married – lives with husband. 3 grown children. AA at Vanderbilt for 1 yr. No substance abuse.

ROS: One yeast infection in last 6 months. Weight stable. No hypoglycemia.

Case Presentation

Case Study

Assessment:“Her diet has been erratic and she has missed several doses of her insulin. She’s lost her motivation.”

Plan:“I emphasized the importance of keeping her glucose under good control and encouraged her to resume her previous successful management. I scheduled her to come back in 4 weeks.”

Case Presentation

A Line of Inquiry◦ “Relapse” in glucose control◦ Causes of Relapse◦ A Taxonomy of Interventions◦ Results of a RCT to prevent Relapse

Implications

Outline

Mean HbA1c (95%CI) before and after Intensive Diabetes Care

6

7

8

9

10

11

type 1 n=244 type2-ins

n=311 type2-noins

n=446

Step 1Objective: Quantify the occurrence of glycemic deterioration AFTER achieving acceptable glucose control had been achieved.

Hypothesis: In individuals who have achieved adequate glucose control, deterioration (“Relapse”) will occur at a rate greater than expected based on previous longitudinal studies.

Relapse in Glucose Control

Retrospective Cohort: N=396 Inclusion:

◦ Initial A1c > 8% and had improved by at least 1% AND final A1c less than 8%

◦ Received f/u primary care at Vanderbilt Primary Outcome (time to event)

◦ A1c > 1% of nadir and exceeds 8%

Study Design and Methods

Natural History of Relapse (n=396)P

roba

bilit

y w

ithou

t R

elap

se

0.0

0.2

0.4

0.6

0.8

1.0

0 6 12 18 24 30 36

Months after Nadir

0.0

0.2

0.4

0.6

0.8

1.0

0 6 12 18 24 30 36

Relapse: Insulin Start

Months after Nadir

Pro

babi

lity

of R

elap

se F

ree

Insulin StartedNoYes

Median time to relapse:34.1 months23.8 months

p=0.045 (Log Rank test)

Cumulative incidence of relapse at 1yr: 25%

Initiation of insulin therapy is the only independent predictor identified: HR 1.96

50% relapse by 30 months Median time to relapse in those who

relapsed is 9 months.

Step 1 Findings


Implications for Primary Care

Outline

Movere: To move

“She’s lost her motivation”

IntentAbility/SkillNormsEnvironmental constraintsAnticipated outcomesSelf-standardsEmotionSelf-efficacy

Fishbein 1991

Behavioral Variance is due to . . .

Step 2Objective: Determine the dispositional and situational variables that contribute to deterioration of glycemic control

Hypothesis : Individuals who successfully complete a diabetes improvement program will be more likely to experience glycemic deterioration if exposed to a life stressor compared to those who are not exposed to a life stressor.

Causes of Relapse

Cross-Sectional Structured Interviews◦ ~ 90 minutes each

Population: N= 89 (convenience sample)◦ 42 who had relapsed and 47 who had not

Timing: within 3 months of relapse Exposure (new life stressor) definition:

any change in financial, relational, health or new responsibility


Baseline Characteristics

Relapse (n=42) Stable (n=47)Age 49 52BMI 31.3 32.4Insulin Use* 63% 49%Duration of DM

7.2 6.6

Female 58% 57%African American*

26% 17%

High School 88% 85%

New Life Stressors

Relapse (n=42) Stable (n=47)

Financial 10% 11%

Relational 19% 15%

Health 17% 11%

New Responsibilities*

45% 23%

Total* 95% 60%

Life stressors, high in both groups, appear to be higher (OR =1.5) in individuals who experience glycemic deterioration

New responsibilities (or competing priorities) appear to be driving the difference

Step 2 Findings


Implications

Outline

Classic Dose Response Curve

Step 3Objective: Identify the domains of variation within DM educational interventions.

Exploratory Hypothesis: High intensity (“dose”) of DM educational interventions will be predictive of better glucose control.

A Taxonomy of DM Educational Interventions

Design: ◦ Literature review and expert input “In what

meaningful ways can DM educational interventions vary?”

◦ Standard meta-analytical and meta-regression techinique

Population: RCTs with glycemic control as an outcome (1990-2000)


Setting: One-on-one, group, family Delivery: Face-to-face,

telecommunication, written material

Teaching method: didactic, goal-setting, cognitive reframing, situational problem solving

Content: diet, exercise, medication adherence, knowledge

Provider: Nurse, RD, psychologist, exercise specialist

Intensity of the intervention: # of episodes, duration of episodes, duration of intervention

Domains of Variation

“Dose” of the Intervention

Meta-Analysis: DM Educational Interventions

Six domains characterize meaningful variation in DM educational interventions

Educational interventions have a modest net effect (0.32%) on HbA1c

No clear effect of educational “dose” on glycemic variation

Step 3 Findings


Implications

Outline

Step 4Objective: To assess the relative effectiveness of 3 maintenance treatments, varying in intensity, for preventing glycemic relapse after acceptable glycemic control is achieved

Hypothesis: A higher frequency of intervention will yield, in a dose-dependant fashion, a lower relapse rate

A RCT to Prevent Relapse

60% of primary care patients are not at A1C goal

Intensive diabetes improvement programs improve glycemic control

Many patients fail to sustain glycemic control after 1-2 years (i.e. relapse) ◦ Biological◦ Behavioral

Achieving Glycemic Control

Case Study

HbA1c in the UKPDS

Adapted from UK Prospective Diabetes Study (UKPDS) Group. Lancet. 1998;352:837-853.

Cross-sectional Median Values (7.0% vs 7.9%)

9

8

7

66.2% upper limit of normal range

ADA target

ADA actionsuggested

00 3 6 9

Years From Randomization12 18

ConventionalIntensive

7.4%

6.6%

8.4%

7.5%

8.7%

8.1%

Med

ian

HbA

1c (

%)

6-3

Case Study

Relapse defined as an A1C≥1%

Approximately 45% of patients relapse within 1 year

76% relapse by 3 years

Median time to relapse was 15.2 months

Glycemic Relapse

Routine contact with providers Obesity, Perri et al, 1984

Behavioral maintenance package◦ Identification of situations that are high risk for slips◦ Training in problem solving to deal with high-risk

situations◦ Actual practice in coping with potential slips or high-risk

situations◦ Development of cognitive coping techniques for

negotiating lapses Alcoholism, Marlatt et al, 1996

Systematic but brief assessment & encouragement

Smoking, Baer et al, 1991

Relapse Prevention: Lessons learned from other diseases

Un-blinded randomized controlled trial◦ Randomization: permuted block scheme

3 arms◦ Least intensive – usual care, control◦ Moderate intensity – Quarterly telephonic contact◦ High intensity – Monthly telephonic contact

Methods: Study Design

Patients with type 2 diabetes who recently completed a diabetes improvement program and achieved glycemic control (A1C decrease of ≥ 1%)

◦ DIP is a 12 week intensive outpatient treatment consisting of education from a CDE NP and RD and medication titration

Population

Phone contact by a nurse practitioner with a referral to a dietitian if nutrition self-care is perturbed

Identify and problem-solve issues arising in self-care behaviors, including diet, physical activity, self-monitoring of blood glucose and medication adherence

Intervention

If no problem in self-care behaviors identified◦ Anticipatory planning◦ Positive reinforcement ◦ Goal-setting

Intervention

If problem in self-care behavior identified◦ Standard problem solving paradigm◦ If cannot identify source of problem

Goal setting was employed Compensation with another self-care behavior

Intervention

Nurse practitioners were to adhere to a set of intervention protocols and guidelines

Intervention fidelity analysis performed to determine adherence to the protocol

Intervention Fidelity

Glycemic relapse◦ Defined as an increase in A1C of ≥ 1% from

baseline

◦ Proportion of relapse at each time point◦ Time to event

Outcome

28 of the participants also had maximally stimulated c-peptide measured throughout the study

Determine the extent of relapse due to decrease in b-cell function

b-Cell function

CharacteristicControlGroup(n=54)

Quarterlycontact(n=55)

Monthlycontact(n=55)

Age, y** 56.2 ± 10 55.7 ± 11 53.5 ± 11

Female (%) 43 38 51

African American (%) 13 29 22

≥ High School (%) 87 89 91

Duration of diabetes, y* 5.5 (0.7,10) 4.0 (0.5,10) 4.0 (0.5,10)

Insulin use (%) 59 45 58

Units of insulin/kg* 39 (24, 79) 59 (32,100) 61 (25, 93)

BMI, kg/m2** 34 ± 7 33 ± 6 35 ± 7

A1C, %** 6.7 ± 0.7 6.6 ± 0.7 6.8 ± 0.6

CES-D* 9 (4,18) 10 (4,17) 7 (4,14)

Baseline Characteristics

No differences between study arms for any characteristic

* Reported as Median (IQR); ** Reported as Mean ± SD

Adherence to Relapse interview protocol quite high◦ 29 calls from 2 NPs analyzed by 2 coders◦ All elements of protocol present at least 80% of

the time

96% of phone calls were completed

Attrition rate 9.2%

Intervention Fidelity

3 months 8%

6 months 14%

12 months 16%

24 months 25%

Overall (at any point in study) 45%

Overall Relapse Rates

0%

5%

10%

15%

20%

25%

30%

35%

3 6 12 18 24

Months

Re

lap

se R

ate

Crude Relapse Rates

Controls MonthlyQuarterly

Controls MonthlyQuarterly

Relapse Free – Survival Analysis

0.00

0.10

0.20

0.30

0.40

0.50

Pro

babili

ty o

f re

lapse

0.25

0.35

0.45

0.55

0.65

0.75

0.85

0.95

Rela

pse

Fre

e

0 6 12 18 24Time to first relapse (months)

Maximally stimulated C-peptide (ng/mL)*

Baseline 7.2 (IQR 5.2, 8.4)

24 months 7.0 (IQR 5.4, 7.9)

b-Cell Function

* p = 0.72 by signed-rank test (non-parametric paired data)

Relapse at 24 months(n=12)

No relapse at 24 months

(n=9)

Delta C-peptide (ng/mL)* 0.18 (-0.7, 2.2) 0.24 (-0.7, 1.2)

b-Cell Function

* median (IQR), p = 0.94 by Wilcoxon rank sum

Quarterly:Control Monthly:Control

Overall 0.96 (0.49 – 1.9) 1.01 (0.52 – 1.9)

FemaleMale

0.4 (0.13 – 1.2)1.69 (0.58 – 4.9)

1.1 (0.4 – 2.7)0.73 (0.26 – 2.1)

BMI < 35 kg/m2

BMI ≥ 35 kg/m2

1.8 (0.71 – 4.7)0.52 (0.18 – 1.5)

2.4 (1.01 – 5.7)0.42 (0.17 – 1.0)

BlackNon-Black

1.1 (0.0024 – 523)1.01 (0.47 – 2.2)

1.6 (0.0037 – 716)0.94 (0.46 – 1.9)

Sub-Group Analysis

Two maintenance strategies employing a telephonic behavioral maintenance strategy did not prevent glycemic relapse more than usual care

Certain sub-groups may have benefited from the intervention◦ BMI ≥ 35 kg/m2 – both intervention arms◦ Females – quarterly contact only

Summary

Lower relapse rate than anticipated from observational studies

Intervention◦ Based on successful maintenance strategies for

other diseases; other programs may prove more effective

◦ No protocol for what to do when someone relapsed

Self-care behavior assessment not sufficient to detect early deterioration

Limitations

Disease management companies use telephonic contact or newsletters in the maintenance phase of disease care

This kind of intervention is understudied – further work is needed to understand maintenance care and who benefits from these interventions

Translation to Practice

Kong Chen, PhD Renee Stiles, PhDAyumi Shintani, PhD Ken Wallston, PhDAnne Brown, ANP Kathleen Wolff, ANPAl Powers, MD Robert Dittus, MDAlan Graber, MD Jim Pichert, PhDTed Speroff, PhD Shelley Ellis, MDFrancine Johnson, MD Jeffrey Bontrager, MDCarolyn Nyuang, MD Michael Blaha, MDStephanie Michon, RD LauraShackleford, FNPDavid Schlundt, PhD Daryl Granner, MD

NIDDK

Acknowledgments

Tom A. Elasy, M.D., M.P.H. Vanderbilt University February, 2012.

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Transcript of Tom A. Elasy, M.D., M.P.H. Vanderbilt University February, 2012.