tom a. elasy, m.d., m.p.h. vanderbilt university february, 2012
TRANSCRIPT
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Diabetes Care: So clear yet so hard
Tom A. Elasy, M.D., M.P.H.Vanderbilt University
February, 2012
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So Clear
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Scalability◦ People◦ Intervention◦ Context
Sustainability◦ Theories◦ Interventions: induction vs. maintenance
Monitoring Goal setting
Yet so hard
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Yarnall KS, et al. Am J Public Health 2003;93:635-641
So hard
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A line of inquiry◦ “Relapse” in glucose control◦ Causes of Relapse◦ A Taxonomy of Interventions◦ Results of a RCT to prevent Relapse
Implications
Outline
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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
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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
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Case Study
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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
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A Line of Inquiry◦ “Relapse” in glucose control◦ Causes of Relapse◦ A Taxonomy of Interventions◦ Results of a RCT to prevent Relapse
Implications
Outline
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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
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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
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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
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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
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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)
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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
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A Line of Inquiry◦ “Relapse” in glucose control◦ Causes of Relapse◦ A Taxonomy of Interventions◦ Results of a RCT to prevent Relapse
Implications for Primary Care
Outline
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Movere: To move
“She’s lost her motivation”
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IntentAbility/SkillNormsEnvironmental constraintsAnticipated outcomesSelf-standardsEmotionSelf-efficacy
Fishbein 1991
Behavioral Variance is due to . . .
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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
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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
Study Design and Methods
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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%
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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%
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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
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A Line of Inquiry◦ “Relapse” in glucose control◦ Causes of Relapse◦ A Taxonomy of Interventions◦ Results of a RCT to prevent Relapse
Implications
Outline
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Classic Dose Response Curve
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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
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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)
Study Design and Methods
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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
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“Dose” of the Intervention
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Meta-Analysis: DM Educational Interventions
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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
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A Line of Inquiry◦ “Relapse” in glucose control◦ Causes of Relapse◦ A Taxonomy of Interventions◦ Results of a RCT to prevent Relapse
Implications
Outline
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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
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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
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Case Study
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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
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Case Study
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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
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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
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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
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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
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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
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If no problem in self-care behaviors identified◦ Anticipatory planning◦ Positive reinforcement ◦ Goal-setting
Intervention
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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
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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
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Glycemic relapse◦ Defined as an increase in A1C of ≥ 1% from
baseline
◦ Proportion of relapse at each time point◦ Time to event
Outcome
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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
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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
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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
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3 months 8%
6 months 14%
12 months 16%
24 months 25%
Overall (at any point in study) 45%
Overall Relapse Rates
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0%
5%
10%
15%
20%
25%
30%
35%
3 6 12 18 24
Months
Re
lap
se R
ate
Crude Relapse Rates
Controls MonthlyQuarterly
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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)
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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)
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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
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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
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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
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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
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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
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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
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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