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Diabetes Multi-Center Research Diabetes Multi-Center Research Consortium (DMCRC)Consortium (DMCRC)

Coordinating CenterCoordinating Center HMO Research Network DEcIDE CenterHMO Research Network DEcIDE Center

PI Joe Selby, MDPI Joe Selby, MD Co-PI Patrick O’Connor MDCo-PI Patrick O’Connor MD

Affiliate CenterAffiliate Center Johns Hopkins University DEcIDE CenterJohns Hopkins University DEcIDE Center

PI Jodi Segal, MDPI Jodi Segal, MD Co-PI Eric Bass, MDCo-PI Eric Bass, MD

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The Case for CER in DiabetesThe Case for CER in Diabetes

HIGH BURDEN OF DISEASEHIGH BURDEN OF DISEASE

– High, rising prevalence of diabetes (>23 High, rising prevalence of diabetes (>23 million diagnosed cases, 10% prevalence million diagnosed cases, 10% prevalence in adults)in adults)

– Chronicity – life expectancy with diabetes Chronicity – life expectancy with diabetes >20 years; age at diagnosis decreasing; >20 years; age at diagnosis decreasing; complication-related morbidities lead to complication-related morbidities lead to many years with high annual costsmany years with high annual costs

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The Case for CER in DiabetesThe Case for CER in Diabetes

UNCERTAINTY UNCERTAINTY Variation in Practice Variation in Practice– Multiple therapeutic choices (6 classes of Multiple therapeutic choices (6 classes of

oral agents, two classes of injectables) oral agents, two classes of injectables)

– Several options are relatively new and costly Several options are relatively new and costly

– Treatments vary in mechanisms of action, Treatments vary in mechanisms of action, relative effectiveness and safety uncertainrelative effectiveness and safety uncertain

– Optimal treatment “strategies” unclear: Optimal treatment “strategies” unclear: timing of pharmacotherapy; treatment timing of pharmacotherapy; treatment targets; sequencing and combination TXtargets; sequencing and combination TX

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The Case for CER in DiabetesThe Case for CER in Diabetes

Complexity in Optimizing EffectivenessComplexity in Optimizing Effectiveness– Self-care, including medication adherence is Self-care, including medication adherence is

central to effectiveness, but difficult to optimizecentral to effectiveness, but difficult to optimize

– Out-of-pocket medication costs interfere with Out-of-pocket medication costs interfere with medication adherence and self-caremedication adherence and self-care

– Blood pressure, lipid control, and aspirin each Blood pressure, lipid control, and aspirin each more effective than “tight” glycemic control in more effective than “tight” glycemic control in preventing most diabetic complicationspreventing most diabetic complications

– Weight management is important, but several Weight management is important, but several medication classes cause weight gainmedication classes cause weight gain

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The Case for CER in DiabetesThe Case for CER in Diabetes

Complexity in Optimizing EffectivenessComplexity in Optimizing Effectiveness– ““Systems Approaches” may enhance self-care Systems Approaches” may enhance self-care

and improve adherence and care coordinationand improve adherence and care coordination

– Depression common in diabetes, but role of Depression common in diabetes, but role of depression therapy in improving control unclear depression therapy in improving control unclear

– Role of “tight” control in preventing CVD Role of “tight” control in preventing CVD complications thrown into question in 2008 by complications thrown into question in 2008 by three RCT’s: ACCORD, ADVANCE, VADTthree RCT’s: ACCORD, ADVANCE, VADT

– Other adverse consequences of tight control - Other adverse consequences of tight control - wt. gain, hypoglycemia, fractureswt. gain, hypoglycemia, fractures

– Benefits may vary by patient age, DM duration Benefits may vary by patient age, DM duration

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The Case for CER in DiabetesThe Case for CER in Diabetes

PREVENTION AND EARLY DETECTION PREVENTION AND EARLY DETECTION

– Reservoir of undiagnosed cases, but the net Reservoir of undiagnosed cases, but the net benefits of screening various populations for benefits of screening various populations for diabetes not entirely cleardiabetes not entirely clear

– Diabetes can be prevented or postponed by Diabetes can be prevented or postponed by lifestyle and/or pharmacotherapy; but optimal lifestyle and/or pharmacotherapy; but optimal “real world” programs not fully clarified“real world” programs not fully clarified

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DataCommittee

ClinicalCommittee

MethodsCommittee

StakeholderCommittee

Administrative Committee

Project Manger

Executive Committee – Includes AHRQ, Coordinating, Affiliate Center Leadership

DMCRC StructureDMCRC Structure

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DataCommittee

ClinicalCommittee

MethodsCommittee

StakeholderCommittee

Administrative Committee

Project Manger

Executive Committee – Includes AHRQ, Coordinating, Affiliate Center Leadership

DMCRC StructureDMCRC Structure

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Expanded Executive CommitteeExpanded Executive Committee

Also includes:Also includes: VanderbiltVanderbilt DEcIDE CenterDEcIDE Center – Marie Griffin – Marie Griffin

MD, PI – Comparative Effectiveness of MD, PI – Comparative Effectiveness of Oral Agents in Type 2 DiabetesOral Agents in Type 2 Diabetes

RTIRTI DEcIDE CenterDEcIDE Center – Suzanne West Ph.D. – Suzanne West Ph.D. – Comparative Effectiveness of Oral – Comparative Effectiveness of Oral Hypoglycemics on Chronic Kidney Disease Hypoglycemics on Chronic Kidney Disease and on Time to Initiation of Maintenance and on Time to Initiation of Maintenance InsulinInsulin

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DMCRC Work AssignmentsDMCRC Work Assignments

1.1. Comparative Effectiveness of Bariatric Surgery vs. Usual Care in Type 2 Comparative Effectiveness of Bariatric Surgery vs. Usual Care in Type 2 Diabetes (two projects)Diabetes (two projects)

2.2. Proposal for New Statistical Briefs - using representative data to characterize Proposal for New Statistical Briefs - using representative data to characterize trends in diabetes treatment and outcomes (joint)trends in diabetes treatment and outcomes (joint)

3.3. Form and Convene Stakeholders’ Group (HMORN)Form and Convene Stakeholders’ Group (HMORN)

4.4. Form and Convene Data Committee (JHU) – with HMORN, Vanderbilt, RTI Form and Convene Data Committee (JHU) – with HMORN, Vanderbilt, RTI participationparticipation

5.5. Comparative Effectiveness Study of Intensive Glycemic Control vs. Less Comparative Effectiveness Study of Intensive Glycemic Control vs. Less Intensive Control in presence vs. absence of tight blood pressure and lipid Intensive Control in presence vs. absence of tight blood pressure and lipid control (two projects)control (two projects)

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DMCRC Stakeholder CommitteeDMCRC Stakeholder Committee

Government Agencies – AHRQ, NIDDK, Government Agencies – AHRQ, NIDDK, CMS, FDA, CDC, VACMS, FDA, CDC, VA

Clinicians – ACP,AAFP, AADEClinicians – ACP,AAFP, AADE

Patients - ADA, individual patient rep.Patients - ADA, individual patient rep.

Expanded DMCRC Executive CommitteeExpanded DMCRC Executive Committee

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Stakeholder - Developed PrioritiesStakeholder - Developed Priorities

1. Role of intensive glucose control in individuals with and without CVD, not typically enrolled in trials

2. Comparative effectiveness of multi-risk factor reduction on long-term CV outcomes

3. Comparison of system-based (coordinated) care vs. usual care

4. Approaches to DX and treatment of depression in diabetes

5. Risk factors for nonadherence – effects of nonadherence on costs and clinical outcomes

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Stakeholder - Developed PrioritiesStakeholder - Developed Priorities

6.6. Effectiveness of eliminating co-pay for effective drugs (statins, ACE-I’s, beta Effectiveness of eliminating co-pay for effective drugs (statins, ACE-I’s, beta blockers, anti-diabetic meds) – on outcomes and total drug burden?blockers, anti-diabetic meds) – on outcomes and total drug burden?

7.7. PPatient reported outcomes, HRQoL in relation to therapy atient reported outcomes, HRQoL in relation to therapy

8.8. Optimal timing for metformin initiation on the continuum of pre-DM -> DMOptimal timing for metformin initiation on the continuum of pre-DM -> DM

9.9. Best strategies for behavior change. Who should do it and where should it Best strategies for behavior change. Who should do it and where should it be done?be done?

10.10. Understanding patient attitudes toward insulin useUnderstanding patient attitudes toward insulin use

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Work Assignment #1:Work Assignment #1:

Health outcomes of bariatric surgery in Health outcomes of bariatric surgery in individuals with type 2 diabetesindividuals with type 2 diabetes

HMORN:HMORN: PI: David Arterburn MD PI: David Arterburn MD (Group Health Cooperative)(Group Health Cooperative)

Johns Hopkins U:Johns Hopkins U: PI: Jodi Segal MD PI: Jodi Segal MD

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WA #1: Primary Aims WA #1: Primary Aims

Compare Compare short-termshort-term outcomes between patients under- outcomes between patients under-going BS and comparable patients who don’tgoing BS and comparable patients who don’t

– Resolution of diabetes (no meds, nl FPG’sResolution of diabetes (no meds, nl FPG’s– Medication useMedication use– BMI ChangeBMI Change– Glycemic, BP, and lipid ControlGlycemic, BP, and lipid Control

Compare Compare longer-termlonger-term outcomes between patients under- outcomes between patients under- going BS and comparable patients who don’t:going BS and comparable patients who don’t:

– Recurrence of diabetes (abnormal labs or re-initiation Recurrence of diabetes (abnormal labs or re-initiation of diabetes medications) of diabetes medications)

– Death, hospitalization, re-operationDeath, hospitalization, re-operation

Examine differences in these outcomes by type of BS: Examine differences in these outcomes by type of BS: Bypass, banding, gastric sleeveBypass, banding, gastric sleeve

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WA #1: Secondary AimsWA #1: Secondary Aims

Compare a variety of shorter- and longer-Compare a variety of shorter- and longer-termterm outcomes outcomes between patients under- going BS and comparable between patients under- going BS and comparable patients who don’t (HMORN and JHU):patients who don’t (HMORN and JHU):– Development and progression of CKD and DNDevelopment and progression of CKD and DN– Development and progression of diabetic retinopathyDevelopment and progression of diabetic retinopathy– Development of incident cardiovascular diseaseDevelopment of incident cardiovascular disease– Long-term health care utilizationLong-term health care utilization– Incidence of various cancersIncidence of various cancers– Incidence of osteoporotic fractureIncidence of osteoporotic fracture– Incidence of urolithiasisIncidence of urolithiasis

Examine differences in these outcomes by type of BS: Examine differences in these outcomes by type of BS: Bypass, banding, gastric sleeveBypass, banding, gastric sleeve

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WA #1: Study Design:WA #1: Study Design:

BSBS MedMed

Mean Age (yrs)Mean Age (yrs) 5454 4747

% Female% Female 5656 8080

Median BMIMedian BMI 4646 3838

Cohort Study in 180,000 patients with evidence of Type 2 diabetes, BMI >35, aged 18-30

Note: presence of BMI in EMR required Approximately 3,100 BS with BMI 2002 – 08

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WA #1: The CohortWA #1: The Cohort

Enters cohort when T2 DM and

BMI > 35 identified Bypass

Banding

Sleeve

No BS2002-2008 2002-2008

BSNo BS

End 2009

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WA #1: Analysis PlanWA #1: Analysis Plan

Propensity Score (time dependent) calculated for each Propensity Score (time dependent) calculated for each cohort membercohort member

Probabilities associated with each decile of PS Probabilities associated with each decile of PS examined, with possible trimming of very low probability examined, with possible trimming of very low probability decilesdeciles

Modeling of outcomes in remaining cohort examined Modeling of outcomes in remaining cohort examined using time-varying predictors for BS and key covariatesusing time-varying predictors for BS and key covariates

For comparisons by type of surgery, separate cohort For comparisons by type of surgery, separate cohort analyses restricted to persons having BS analyses restricted to persons having BS

Treatment heterogeneity examined by age group, Treatment heterogeneity examined by age group, presence of prior comorbid conditionspresence of prior comorbid conditions

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WA #1: Key Points in Analysis WA #1: Key Points in Analysis

Multi-variable models predicting outcome will Multi-variable models predicting outcome will NOT use PSNOT use PS

For discrete analyses, models will evaluate For discrete analyses, models will evaluate non-non-proportionalproportional (i.e., time-varying hazards) (i.e., time-varying hazards)

Will also examine effect heterogeneity by year of Will also examine effect heterogeneity by year of surgery and volume of surgeonsurgery and volume of surgeon

Many more BS patients without pre-surgical BMI, Many more BS patients without pre-surgical BMI, who may contribute to some analyses where BMI who may contribute to some analyses where BMI less likely to confound.less likely to confound.