evaluate cardiovascular safety for glucose lowering … › assets › 504 › CVOTs in...

1) Evaluate the mechanisms linking diabetes, heart failure, and cardiovascular disease.

2) Examine the evolution of T2D drug development and factors leading to the requirement to evaluate cardiovascular safety for glucose lowering therapies.

3) Appraise new and emerging CVOT data for glucose lowering therapies and compare available CVOT data within the T2D therapeutic classes.

4) Compare and contrast CVOT data with updated guideline recommendations and discuss management and prevention strategies in patients with HF and/or CVD.

5) Using a case-based approach, explore unanswered questions and clinical challenges in applying CVOT data to real-world patient care.

6) Recognize opportunities for cardiologists to collaborate with endocrinologists, primary care providers, and other members of the healthcare team to improve outcomes for patients with T2D, HF, and CVD.

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Disclaimer

Special Thanks!

• Supported through an independent educational grant from AstraZeneca.

• Presented by Creative Educational Concepts, Inc. (CEC).

Faculty

Marc S. Sabatine, MD, MPHChairman, TIMI Study GroupLewis Dexter, MD Distinguished Chair in Cardiovascular MedicineProfessor, Harvard Medical SchoolBoston, Massachusetts

Disclosures: Consultant for Amgen, AstraZeneca, and Bristol-Myers Squibb.

Adrian F. Hernandez, MD, MHSVice Dean for Clinical ResearchDuke University School of MedicineProfessor of Medicine, CardiologyDuke Clinical Research InstituteDurham, North Carolina

Disclosures: Receives research funding from the American Heart Association (AHA), AstraZeneca, GlaxoSmithKline, Merck & Co., Luitpold; National Heart, Lung, and Blood Institute (NHLBI), Novartis, Patient-Centered Outcomes Research Institute (PCORI), Verily. Consultant for AstraZeneca, Bayer, Boston Scientific, Boehringer-Ingelheim, Merck & Co., Novartis, Pfizer, Inc.

Faculty

Silvio E. Inzucchi, MDProfessor of MedicineClinical Chief, Section of EndocrinologyYale University, School of MedicineMedical Director, Yale Diabetes CenterYale-New Haven HospitalNew Haven, Connecticut

Disclosures: Consultant for AstraZeneca, Boehringer Ingelheim, Eisai, Novo Nordisk, andSanofi/Lexicon. Receives other financial/material support from Intarcia.

Faculty

BEYOND GLYCEMIC CONTROL

Examining the Link Between Diabetes and CV Disease

Silvio E. Inzucchi, MDSection of EndocrinologyYale School of MedicineNew Haven, Connecticut

Beyond Glucose: Diabetes and CVD Link

† 2° outcome

1. DM and CVD: Epidemiology and mechanisms

2. Impact of glucose lowering and CV outcomes

3. Current landscape of T2D therapies

4. Regulatory mandates

Diabetes and CV Disease

Emergent Risk Factor Collaboration. Lancet. 2010.

N: 698,782

• Diabetes confers about a two-fold excess risk for coronary heart disease

• Analysis based on 530,083 participants from102 prospective studies

• HR adjusted for age, smoking status, BMI, systolic BP, sex and trial arm

Association between HbA1c and Complications in the UKPDS

0

10

20

30

40

50

60

Myocardial Infarction Microvasccular Disease

5.5%

6.5%

7.5%

8.5%

9.5%

10.5%

HbA1c

Stratton IM, et al. BMJ. 2000.

Ad

just

ed In

cid

ence

per

10

00

pat

ien

t-ye

ars

Epidemiological Analysis

Proposed Links between DM and ASCVD

Libby P, Plutzky J. Circulation. 2002.

Gilbert RE, Krum H. Lancet 2015.

DM, Prevalence of HF and Association with HbA1c

Marwick TH, et al. J Am Coll Cardiol. 2018.

Diabetic Heart FailureInteractions of Systemic, Myocardial, and Cellular Manifestations

Diabetes

Impaired glucose handling insulin

resistance

Oxidative Stress

Inflammation Hypertension

Atherosclerosis

Autonomic Dysfunction

Fibrosis↓ Perfusion

CAD

Hypertrophy Apoptosis

∆ Glucose Utilization∆ Fatty Acid Utilization∆ EC Coupling↓ Mitochondrial Function

Diastolic Dysfunction Systolic Dysfunction

Diabetic Heart Failure

↓ Compliance

CardiomyocytesMyocardium

Systemic


† 2° outcome





Adapted from Bergenstal RM, et al. Am J Med. 2010; Duckworth W, et al. N Engl J Med. 2009; Gerstein HC, et al. N Engl J Med.2008; Hayward RA, et al. N Engl J Med. 2015; Holman RR. N Engl J Med. 2008; Nathan DM, et al. N Engl J Med. 1993;

Nathan DM, et al. N Engl J Med. 2005; Orchard TJ, et al. JAMA. 2015; Patel A, et al. N Engl J Med. 2008; UKPDS Group. Lancet. 1998; Zoungas S, et al. N Engl J Med. 2014.

Impact of Intensive Glucose-Lowering Therapy in DM Summary of Major RCTs

Study Microvasc CVD Mortality

DCCT(A1c 7.2 vs. 9.1%) ➔ ➔

UKPDS 33(A1c 7.0 vs. 7.9%) ➔ ➔

ACCORD(A1c 6.4% vs. 7.5%) ➔

ADVANCE(A1c 6.3% vs. 7.0%) ➔ ➔

VADT (A1c 6.9% vs. 8.4%) ➔ ➔

Study Microvasc CVD Mortality

DCCT(A1c 7.2 vs. 9.1%) ➔ ➔

UKPDS 33(A1c 7.0 vs. 7.9%) ➔ ➔

ACCORD(A1c 6.4% vs. 7.5%) ➔

ADVANCE(A1c 6.3% vs. 7.0%) ➔ ➔

VADT (A1c 6.9% vs. 8.4%) ➔ ➔

➔

➔

➔

➔

➔

Initial Randomized Trial

Long Term Follow-up

*Major CV events defined as CV death or non-fatal stroke or non-fatal myocardial infarction

More Intensive Glycemic Control Has Modest Effect on ASCVD and None on HF Outcomes

Turnbull FM, et al. Diabetologia. 2009.

Trials

Number of events(annual event rate, %) ∆HbA1c

(%)HR

(95% CI)Overall HR

(95% CI)More intensive Less intensive

Major cardiovascular events*

ACCORD 352 (2.11) 371 (2.29) -1.01

ADVANCE 557 (2.15) 590 (2.28) -0.72

UKPDS 169 (1.30) 87 (1.60) -0.66

VADT 116 (2.68) 128 (2.98) -1.16

Overall 1194 1176 -0.88 0.91 (0.84, 0.99)

Stroke

Overall 378 370 -0.88 0.96 (0.83, 1.10)

Myocardial infarction

Overall 730 745 -0.88 0.85 (0.76, 0.94)

Hospitalised/fatal heart failure

Overall 459 446 -0.88 1.00 (0.86, 1.16)

0.5 1 2

Favours more intensive

Favours less intensive

The Puzzles of Diabetesand Its Complications

Glucose Smoking BP

Genetics Inflammation Obesity

Insulin Resistance

Age Lipids

MACROvascular Complications

Genetics Glucose BP

MICROvascular Complications

Fruchart JC. Circulation. 2004; Yau JW, et al. Diabetes Care. 2012; MJ Fowler. Clin Diabetes. 2008.


† 2° outcome





Adapted from Inzucchi SE, Sherwin RS. Cecil Medicine. 2011.

Multiple Pathophysiological Defects in T2D+

-

-

peripheralglucose uptake

hepatic glucose production

pancreatic insulinsecretion

pancreatic glucagonsecretion

gutcarbohydratedelivery &absorption

incretineffect

HYPERGLYCEMIA?

renal glucose excretion

Pathophysiologic Progression of T2D(and Its Vascular Complications)

Adapted from Ramlo-Halsted BA, et al. Clin Diabetes.2000.

Re

lati

ve f

un

ctio

n

Time (years)

β-cell failure

0

50

100

150

200

250

–10 –5 0 5 10 15 20 25 30

IFGIGTOBESITY

Glu

cose

(m

g/d

L)

DM diagnosis

50

100

150

200

250

300

350

MICROVASCULAR COMPLICATIONS

MACROVASCULAR COMPLICATIONS

UNCONTROLLED HYPERGLYCEMIAT2D


Multiple Pathophysiologically-Based Therapies for T2D

+

-

-






incretineffect

HYPERGLYCEMIA?

TZDsMetformin

DPP-4 inhibitors

GLP-1 Ragonists

SUs

Insulin


SGLT2 inhibitors

A G I s

Glinides

Amylinmimetics

DA agonists

Bile acidsequestrants


+

-

-






incretineffect

HYPERGLYCEMIA?

TZDsMetformin

DPP-4 inhibitors

GLP-1 Ragonists

SUs

Insulin


SGLT2 inhibitors

Major Pathophysiologically-Based Therapies for T2D

“insulin

providers”

“incretin

enhancers”

“insulin

sensitisers”

“glucose

excreter”

SUs

Insulin

DPP-4

inhibitors

GLP-1 R

agonists

TZDsMetformin

SGLT2

inhibitors

Oral Class Mechanism Advantages Disadvantages Cost

Metformin • Activates AMP-kinase / mGMP (?other)• Hepatic glucose production

• Extensive experience• No hypoglycemia• Weight neutral• ? CVD

• Gastrointestinal• Lactic acidosis• B-12 deficiency• Contraindications

Low

Sulfonyl-ureasGlimepirideGlipizideGlyburide

• Closes KATP channels• Insulin secretion

• Extensive experience• Microvascular risk

• Hypoglycemia• Weight• Low durability• ? Blunts ischemic preconditioning• Uncertain CV safety

Low

TZDsPioglitazoneRosiglitazone

• PPAR-g activator• Insulin sensitivity

• No hypoglycemia• Durability• TGs*• HDL-C • ? ASCVD events*

• Weight • Edema/Heart Failure• Bone fractures• LDL-C†

• ? Bladder cancer• ? Macular edema

Low

Inzucchi SE, et al. Diabetes Care. 2015; Davies MJ, et al. Diabetes Care. 2018.

* Pioglitazone † RosiglitazoneProperties of glucose-lowering agents (before CVOTs)

*Canagliflozin

Oral Class Mechanism Advantages Disadvantages Cost

DPP-4InhibitorsSitagliptinSaxagliptinAlogliptinLinagliptin

• Inhibits DPP-4• Increases incretin(GLP-1, GIP) levels

• No hypoglycemia• Well-tolerated

• Angioedema / urticaria• ? Pancreatitis• ? Arthralgia• ? Bullous pemphigoid

High

SGLT2inhibitorsCanagliflozinDapagliflozinEmpagliflozinErtugliflozin

• Inhibits SGLT2 in proximal nephron• Increases glucosuria

• No hypoglycemia• Weight• BP• TGs• HDL-C• Albuminuria• Effective at all stages of disease

• GU infections• DKA (rare)• Polyuria• UTI• Volume depletion• Cr (transient)• ? AKI• LDL-C • ↑risk for fractures*• ↑risk for amputation*• Fournier's gangrene (rare)

High

Properties of glucose-lowering agents (before CVOTs)

Inzucchi SE, et al. Diabetes Care. 2015; Davies MJ, et al. Diabetes Care. 2018.

Normal Physiology of Renal Glucose Homeostasis

SGLT2 SGLT1

Proximal tubule

S1

GlomerulusDistal tubule

Glucosefiltration

Minimalglucose

excretion

S3

Collecting duct

90%

10%Glucose

reabsorption

Loop of Henle

Adapted from Wright EM. Am J Physiol Renal Physiol. 2001; Lee YJ, et al. Kidney Int Suppl. 2007; Han S. Diabetes. 2008.

SGLT2 SGLT1

Proximal tubule

S1


Glucosefiltration

Increasedglucose

excretion

S3

Collecting duct

90%

10%Glucose

reabsorption

Loop of Henle- 70-80 g/day

( - 280-320 kcal/day)

SGLT2 inhibitor

SGLT2 Inhibition ReducesRenal Glucose Reabsorption


InjectableClass

Mechanism Advantages Disadvantages Cost

GLP-1-R agonistsExenatideLiraglutideAlbiglutideDulaglitudeLixisenatideSemaglutide

• Activates GLP-1 R• Insulin• Glucagon• Gastric emptying• Satiety

• Weight• No hypoglycemia• PP glucose• CV risk factors

• Gastrointestinal• Injectable• Heart rate• ? Pancreatitis• ? Medullary cancer (mice only)• Training required

High

InsulinDegludecGlargineDetemirNPHRegularLisproAspartGlulisine

• Activates insulin receptor• Myriad

• Universally effective• Unlimited efficacy• Microvascular risk

• Hypoglycemia• Weight gain• Injectable• ? Mitogenicity• Patient reluctance• Training required

Varies

Properties of glucose-lowering agents (before CVOTs)Inzucchi SE, et al. Diabetes Care. 2015; Davies MJ, et al. Diabetes Care. 2018.

The Enteroinsular Axis

Gut Insulin(GLP-1,GIP)

Glucagon(GLP-1)

Nutrient signals

Hormonal signals• GLP-1• GIP

Neural signals

Adapted from Creutzfeldt W. Diabetologia. 1979; Kieffer T, et al. Endocr Rev. 1999; Nauck MA, et al. Diabetologia. 1993.

β cells

DPP-4 Inhibitor

α cells

+ Delays gastric emptying+ Decreases appetite (CNS)

Previous 2015 ADA-EASD Position Statement Management of Hyperglycemia in T2D

Anti-hyperglycemic TherapyGlycemic Targets

• HbA1c <7.0% (mean PG 150–160 mg/dL)

• Pre-prandial PG <130 mg/dL

• Post-prandial PG <180 mg/dL

• Individualization is key

• Tighter targets (6.0%–6.5%)—younger, healthier

• Looser targets (7.5%–8.0%+)—older, comorbidities, hypoglycemia prone, etc.

• Avoidance of hypoglycemia

PG = plasma glucose Inzucchi SE, et al. Diabetes Care. 2015; Inzucchi SE, et al. Diabetologia.2015.

† 2° outcome

Beyond GlucoseDM and CVD Link

1. DM and CVD: Epidemiology and mechanisms2. Impact of glucose lowering and CV outcomes3. Current landscape of T2D therapies4. Regulatory mandates

Class Potential CV Benefit* Potential CV Concern

Insulin •Anti-inflammatory•Hypoglycemia•Weight gain•? Mitogenicity

SU’s —•Hypoglycemia•Weight gain• ischemic preconditioning

Metformin • LDL-C• CRP

•Lactic acidosis in advanced HF

TZD’s• Insulin• TG, HDL-C• CRP•Direct vascular effects (PPAR-g)

•Salt/fluid retention•Weight gain• LDL-C

DPP-4 i’s •? Indirect cardiac effects (via GLP-1)•? Direct vascular effects

—

GLP-1 RA’s•Weight loss• BP• TG•? Direct cardiac effects

• Heart rate

SGLT2-i’s•Weight loss• BP• albuminuria• uric acid

•Hypovolemia• LDL

Effects of DM Meds on the CV System

*beyond glucose-lowering Lathief S, Inzucchi SE. Trends Cardiovasc Med. 2016.

Heart Attack Risk Seen in Drug for Diabetes

Tuesday, May 22, 2007

Courtesy of Darren McGuire, MD UT Southwestern, 2015; https://www.fda.gov/downloads/Drugs/Guidances/ucm071627.pdf.

“…sponsors should demonstrate that the therapy will not result in an unacceptable increase in cardiovascular risk.”

• Meta-analysis strategy using Phase 2/3 data

• Blinded central adjudication of CVD events

• Inclusion of high-risk subjects: advanced CVD, elderly, CKD

• Minimum exposure of 2 years in large CVOT

• Approximately 15,000 pt-yrs

1.0

Hazard Ratio

1.81.3

Pre-marketing AnalysesUpper CL of 95% CI <1.8For a HR=1.0 ➔ ≈122 events

Post-marketing AnalysesUpper CL of 95% CI <1.3For a HR=1.0 ➔ ≈611 events

Classes Generic Names A1c Impact on CVD

InsulinDegludec, Glargine, Detemir, NPH, Regular, Lispro, Aspart, Glulisine

No limit

SU’sGlyburide, Glipizide, Glimepiride

1%–1.5%

MetforminMetformin

1%–1.5%

TZD’sRosiglitazone, Pioglitazone

1%–1.5%

DPP-4 i’sSitagliptin, Saxagliptin, Alogliptin, Linagliptin

0.5%–1%

GLP-1 RA’sExenatide, Liraglutide, Albiglutide, Dulaglutide, Lixisenatide

1%–1.5%

SGLT2-i’sCanagliflozin, Dapagliflozin, Empagliflozin, Ertugliflozin

0.5%–1%

DM Meds and CV Outcomes Pre-FDA Guidance

*small studies; low-risk populations; MI only † 2° outcome

PRE

POST

FDA GUIDANCE

Classes Generic Names A1c Impact on MACE


No limit ➔


1%–1.5% ➔

MetforminMetformin

1%–1.5% *


1%–1.5% ➔ – †


0.5%–1% ?


1%–1.5% ?


0.5%–1% ?*small studies; low-risk populations; MI only † 2° outcome


Classes Generic Names A1c Impact on HF


No limit ➔


1%–1.5% ➔

MetforminMetformin

1%–1.5% ➔


1%–1.5%


0.5%–1% ?


1%–1.5% ?


0.5%–1% ?


1. People with diabetes are at increased risk for ASCVD and HF.

2. However, correcting diabetes’ major metabolic defect—hyperglycemia—has had little effect on reducing these complications.

3. Glucose-lowering medications could pose potential benefits and/or potential risks to the CV system.

4. Until recently the impact of older drugs themselves (i.e., beyond glucose-lowering) on actual CV outcomes in T2D patients has been either neutral or inconsistently demonstrated.

5. In 2008, the FDA provided guidance to industry to conduct large CV outcome trials in order ensure that new diabetes therapies would at least safe for the heart.

6. Over the past 3 years, we have seen important new results from these trials….

Summary

DECIPHERING CARDIOVASCULAR OUTCOME

TRIALS FOR DIABETES THERAPIES

How Do CVOTs Compare?

Marc S. Sabatine, MD, MPHChairman, TIMI Study Group

Lewis Dexter, MD, Distinguished Chair in Cardiovascular Medicine, BWHProfessor of Medicine, HMS

Disclosures

• Consultant for Amgen, AstraZeneca, and Bristol-Myers Squibb

HR (95% CI) HR (95% CI) P value

SAVOR-TIMI 53 1.00 (0.89, 1.12) 0.99

EXAMINE 0.96 (n/a, 1.16) 0.32*

TECOS 0.99 (0.89, 1.11) 0.84

CARMELINA 1.02 (0.89, 1.17) 0.7398

0.5 1.0 2.0

Favors DPP-4 inhibitor Favors placebo

3P-MACE

HR (95% CI) HR (95% CI) P value

1.27 (1.07, 1.51) 0.007

1.19 (0.89, 1.59) 0.24

1.00 (0.83, 1.20) >0.99

0.90 (0.74, 1.08) 0.2635

Hospitalization for Heart Failure

DPP4 Inhibitors CVOTs• SAVOR-TIMI 53 (saxagliptin)

• 16,492 patients w/CVD or multiple risk factors

• EXAMINE (alogliptin)• 5380 patients w/ACS

Scirica BM, et al. N Engl J Med. 2013; White WB, et al. N Engl J Med. 2013; Zannad F, et al. Lancet. 2015; Green JB, et al. N Engl J Med. 2015; McGuire DK, JAMA Cardiol. 2016; Rosenstock J, et al. Cardiovasc Diabetol. 2018; Rosenstock J, et al. Oral Presentation EASD 2018.

• TECOS (sitagliptin)• 14,671 patients w/CVD

• CARMELINA (linagliptin)• 7003 patients w/CVD and/or kidney disease

*One-sided P-value 0.5 1.0 2.0

Favors DPP-4 inhibitor Favors placebo

GLP-1 Receptor Agonist CVOTs

Drug Trial N Pts w/ASCVD Follow-up

Lixisenatide ELIXA 6068100%

(post-ACS)2.1 yrs

Liraglutide LEADER 9340 81% 3.8 yrs

Semaglutide SUSTAIN-6 3297 59% 2.1 yrs

Exenatide EXSCEL 14,752 73% 3.2 yrs

AlbiglutideHARMONY Outcomes

9463 100% 1.6 yrs

Dulaglutide REWIND 9901 31% ~6.5 yrs

Pfeffer MA, et al. N Engl J Med. 2015; Marso SP, et al; LEADER Trial Investigators. N Engl J Med. 2016; Marso SP, et al; SUSTAIN-6 Investigators. N Engl J Med. 2016; Holman RR, et al. N Engl J Med. 2017.Hernandez AF, et al. Lancet. 2018; Gerstein HC, et al. Diabetes Obes Metab. 2018; www.clinicaltrials.gov.

ELIXA

CV

Dea

th, M

I, S

tro

ke, H

osp

. fo

r U

A(%

of

Pati

ents

)

MonthsPfeffer MA, et al. N Engl J Med. 2015.

Hazard ratio, 1.02 (95% CI, 0.89-1.17)

Lixisenatide

Placebo

Non-ACS GLP-1 RA CVOTsC

V D

eat

h, M

I, S

tro

ke(%

of

pat

ien

ts)

Years

EXSCEL

Marso SP, et al; LEADER Trial Investigators. N Engl J Med. 2016; Marso SP, et al; SUSTAIN-6 Investigators. N Engl J Med. 2016; Holman RR, et al. N Engl J Med. 2017.Hernandez AF, et al. Lancet. 2018.

CV

De

ath

, MI,

Str

oke

(% o

f p

atie

nts

)

LEADER SUSTAIN-6

Months Weeks

HARMONYOutcomes

Months

Summary of GLP-1 RA CVOT Results

Drug TrialRelative Risk Reduction

MACE CV Death MI Stroke HHF

Liraglutide LEADER 13% 22% 14% 14% 13%

Semaglutide SUSTAIN-6 26% 2% 26% 39% 11% ↑

Exenatide EXSCEL 9% 12% 3% 15% 6%

AlbiglutideHARMONY Outcomes

22% 7% 25% 14% ~25%

Overall, ~15% relative risk reduction in MACE

Marso SP, et al; LEADER Trial Investigators. N Engl J Med. 2016; Marso SP, et al; SUSTAIN-6 Investigators. N Engl J Med. 2016; Holman RR, et al. N Engl J Med. 2017.Hernandez AF, et al. Lancet. 2018.

SGLT2 SGLT1

Proximal tubule

S1


Glucosefiltration

Increasedglucose

excretion

S3

Collecting duct

90%

10%Glucose

reabsorption

Loop of Henle- 70-80 g/day

( - 280-320 kcal/day)

SGLT2 inhibitor

SGLT2 Inhibition ReducesRenal Glucose Reabsorption


EMPA-REG OutcomePrimary MACE Outcome

Zinman B, et al. N Engl J Med. 2015.

Month

HR: 0.86 (95.02% CI: 0.74-0.99)P=0.04 for superiority

0 6 12 18 24 30 36 42 48

20

15

10

5

0

Pat

ien

ts W

ith

an

Eve

nt

(%)

Empagliflozin

Placebo

CV Death, MI, or Stroken=7020 patients, all with CVD

CV Death, MI and StrokePatients with event/analysedEmpagliflozin Placebo HR (95% CI) p-value

3-point MACE 490/4687 282/2333 0.86 (0.74, 0.99) 0.0382

CV death 172/4687 137/2333 0.62 (0.49, 0.77) <0.0001

Non-fatal MI 213/4687 121/2333 0.87 (0.70, 1.09) 0.2189

Non-fatal stroke 150/4687 60/2333 1.24 (0.92, 1.67) 0.1638

0.25 0.50 1.00 2.00

Favours empagliflozin Favours placebo

Empagliflozin and CV Outcomesn=7020 Patients with T2D and CVD

Zinman B, et al. N Engl J Med. 2015.

EMPA-REG OutcomeCV Death/Hospitalization for Heart Failure

Month

n=7020 Patients with T2D and CVD

Placebo

Empagliflozin

HR: 0.66 (95% CI: 0.55-0.79)P<0.001

0 6 12 18 24 30 36 42 48

15

10

5

0

Pat

ien

ts W

ith

an

Eve

nt

(%)

Zinman B, et al. N Engl J Med. 2015; Fitchett D, et al. Eur Heart J. 2016.

5.7%

8.5%

No. of patients

Empagliflozin

Placebo 2333 2271 2226 2173 1932 1424 1202 775 1684687 4614 4523 4427 3988 2950 2487 1634 395

CANVAS Primary MACE Outcome

No. ofpatients

Placebo

Canagliflozin

2 3 4

Hazard ratio 0.86 (95% CI, 0.75-0.97) P<0.0001 for noninferiorityP=0.0158 for superiority

Placebo

Canagliflozin

Intent-to-treat analysis

5 61

20

18

16

14

12

10

8

6

4

2

00

Pat

ien

tsw

ith

ane

ven

t(%

)

4347 4153 2942 1240 1187 1120 789

5795 5566 4343 2555 2460 2363 1661Neal B, et al. N Engl J Med. 2017.

CV Death, Nonfatal MI, or Nonfatal Stroke

Years since randomization

Pat

ien

tsw

ith

anev

ent

(%)

No. ofpatientsPlacebo

Canagliflozin

4347 4202 3015 1281 1242 1184 831

5795 5655 4442 2647 2577 2503 1782

CANVASCV Death or Hospitalization for Heart Failure

Neal B, et al. N Engl J Med. 2017; Rådholm K, et al. Circulation. 2018.

2 3 4

Hazard ratio 0.78 (95% CI, 0.67-0.91)P=0.002

Intent-to-treat analysis

Years since randomization

0 1 5 6

20

18

16

14

12

10

8

6

4

2

0

Placebo

Canagliflozin

CANVASSecondary (66%) vs Primary (33%) Prevention

Mahaffey KW, et al. Circulation.2018.

DAPAGLIFLOZIN10 mg DAILY

PLACEBO

DURATIONEVENT DRIVEN≥1390 MACE

Median follow-up4.2 years

RANDOMIZE 1:1DOUBLE BLIND

All other DM Rx per treating MD

Wiviott SD, et al. Abstract 19485. Presented at AHA Scientific Sessions 2018; Wiviott SD, et al. N Engl J Med. 2018.

17,160 with Type 2 DMEstablished CV Disease (6974) or

Multiple Risk Factors (10186)

Follow-up visits In Person Q 6 mo/ telephone Q 3 mo

Primary EndpointsSafety: MACE (CV Death/MI/Ischemic Stroke)

Dual Efficacy: CV Death/HHF, MACE

DECLARE-TIMI 58Trial Design

HHF=hospitalization for heart failure

Full Trial CohortN=17,160

Age, yrs, Mean (SD) 64 (7)

Female Sex (%) 37

BMI, Mean (SD) 32 (6)

Duration of T2DM, yrs, Median (IQR) 11 (6, 16)

HbA1c (%), Mean (SD) 8.3 (1.2)

eGFR (CKD-EPI), Mean (SD) 85 (16)

Region (%): North America 32

Europe 44

Latin America 11

Asia Pacific 13

Established CV Disease (%) 41

History of Heart Failure (%) 10

DECLARE-TIMI 58Baseline Characteristics

P=NS for all between treatment arm comparisons


DECLARE TIMI-58Primary Endpoints

MACECV Death/HHF

DapagliflozinPlacebo

8.8% vs 9.4%HR 0.93 (0.84-1.03)P(Noninferiority) <0.001P(Superiority) 0.17

4.9% vs 5.8%HR 0.83 (0.73-0.95)P(Superiority) 0.005

HHF=hospitalization for heart failureWiviott SD, et al. Abstract 19485. Presented at AHA Scientific Sessions 2018; Wiviott SD, et al. N Engl J Med. 2018.

DECLARE-TIMI 58Secondary Endpoints

Renal Composite Endpoint 40%↓ eGFR, ESRD, Renal or CV death

4.3% vs. 5.6%HR 0.76 (0.67-0.87)P<0.001

All-Cause Mortality

6.2% vs 6.6%HR 0.93 (0.82-1.04)P=0.20


DECLARE TIMI-58Endpoints and Components

Dapagliflozin Placebo

*P for superiority, **P for non-inferiority


EMPA-REG OUTCOME CANVAS Program DECLARE-TIMI 58

Median Follow-Up Time (yrs) 3.1 2.4 4.2

Trial participants (n) 7020 10142 17160

Age (mean) 63.1 63.3 63.9

Female Sex 2004 (28.5%) 3633 (35.8%) 6422 (37.4%)

Established ASCVD 7020 (100%) 6656 (66%) 6974 (41%)

History of Heart Failure 706 (10.1%) 1461 (14.4%) 1724 (10.0%)

eGFR <60 ml/min/1.73 m2 1819 (25.9%) 2039 (20.1%) 1265 (7.4%)

Baseline Characteristics

Zinman B, et al. N Engl J Med. 2015; Neal B, et al. N Engl J Med. 2017; Wiviott SD, et al. N Engl J Med. 2018; Zelniker TA, et al. Lancet. 2018.

Meta-Analysis of CVOTsMACE by Presence of ASCVD

Test for Subgroup Differences P=0.05

Hazard RatioZelniker TA, et al. Lancet. 2018.

Meta-Analysis of CVOTsCV Death/HHF by Presence of ASCVD


CV Death/HHF

Hazard RatioZelniker TA, et al. Lancet. 2018.

Meta-Analysis of CVOTsCV Death/HHF by History of Heart Failure


CV Death/HHF

Hazard Ratio Zelniker TA, et al. Lancet. 2018.

Meta-Analysis of CVOTsCV Death/HHF by Baseline eGFR

P-trend 0.007Hazard Ratio Zelniker TA, et al. Lancet. 2018.

Adrian F. Hernandez, MD, MHSVice Dean for Clinical Research

Duke University School of MedicineProfessor of Medicine, Cardiology

Duke Clinical Research InstituteDurham, North Carolina

FROM CLINICAL TRIALS TO CLINICAL PRACTICE

Applying CVOT Data to Real-World Patient Care

Disclosures

• Research funding: American Heart Association (AHA), AstraZeneca; GlaxoSmithKline; Merck & Co.; Luitpold; National Heart, Lung, and Blood Institute (NHLBI); Novartis; Patient-Centered Outcomes Research Institute (PCORI); Verily• Consultant: AstraZeneca; Bayer; Boston Scientific;

Boehringer-Ingelheim; Merck & Co.; Novartis; Pfizer, Inc.

Should we aim to improve population health?

Should we take 17 years to translate evidence into

practice?

† 2° outcome

Evidence into Practice

1. Bending the population health curve2. Quality chasm3. Implementation strategies4. Following evidence into practice

0

100

200

300

400

500

600

700

2015 2040

Globally, 415 million people are living with diabetes.

Type 2 Diabetes is Increasingly Prevalent

+55%

http://diabetesatlas.org/resources/2017-atlas.html.

By 2040, people with diabetes is estimated to grow to 642 million.

Some places, especially along both coasts, experienced larger increases in life expectancy between 1980 and 2014.

In contrast, other places saw little, if any, improvement in life expectancy over this same period.

Change in Life Expectancy at Birth by County1980 to 2014

Dwyer-Lindgren L, et al. JAMA Intern Med. 2017.

“An Ounce of Prevention is Pound of Cure”

Diabetes mellitus increases the risk of HF • ≈2-fold in men • ≈5-fold in women

Heidenreich PA, et al. Circ Heart Failure. 2013; Horwitch TB, Fonarow GC. JAMA Cardiol. 2017.

Would Prevention be Easier for These Patients?

A 60-year-old male with a long history of heart failure and 3 weeks of gradually worsening symptoms.BP: 85/40 mmHg

An 80-year-old female with a long history of hypertension and multiple admissions for sudden onset dyspnea.BP: 185/120 mmHg

Heart Failure Hospitalization Rate2013–2015

This map was created using the Interactive Atlas of Heart Disease and Stroke, a website developed by the Centers for Disease Control and Prevention. Division for Heart Disease and Stroke Prevention. http://cdc.gov/dhdsp/map/atlas.

Costs and Accountable Care!

$2.7 Trillion Is Spent Annually on Health Care Costs (18% of US GDP)

Cardiovascular Disease Costs• Over $445 billion today • $1 trillion by 2030

Heart Failure Costs• Over $31 billion today • $71 billion by 2030

Heidenreich PA, et al. Circ Heart Failure. 2013.

DeVore AD, et al. J Am Coll Cardiol. 2016.

Health Policy Changes Have Greatly Impacted Quality Improvement Programs

† 2° outcome



It takes an average of 17 years for new knowledge generated by randomized controlled trails to be incorporated into practice, and even then application is highly uneven.

From Evidence to Routine Practice

Institute of Medicine (US) Committee on Quality of Health Care in America. National Academies Press (US). 2001.

Quality Improvement Interventions Today

CLINICHOSPITAL

Guidelines—Why No Progress?

Fonarow GC. Rev Cardiovasc Med. 2006.

Who is responsible?

HumblingA complete and utter failure to change care…

Devore AD, et al. Circ Cardiovasc Qual Outcomes. 2015.

† 2° outcome



ADA-EASD Consensus Report 2018Glucose-lowering Medication in T2D – Overall Approach

Davies MJ, et al. Diabetes Care. 2018.

First-line therapy is metformin and comprehensive lifestyle (including weight management and physical activity)If HbA1c above target proceed as below:

Established ASCVD or Heart Failure/CKD

ASCVD Predominates

If HbA1c above target

If further intensification is required or patient is now unable to tolerate GLP-1 RA and/or SGLT-2i, choose agents demonstrating CV safety:

• Consider adding the other class (GLP-1 RA and/or SGTL2i with proven CVD benefit*

• DPP-4i if not on GLP-1 RA

• Basal Insulin

• TZD

• SU

GLP-1 RA with proven CVD benefit*

SGLT-2i with proven CVD benefit* if eGFR adequate

EITHER/OR

Heart Failure (HF) or CKD Predominates

If HbA1c above target

• Avoid TZD in the setting of HF

Choose agents demonstrating CV safety:

• Consider adding the other class with proven CVD benefit*

• DPP-4i (not saxagliptin) in the setting of HF (if not on GLP-1 RA)

• Basal Insulin

• SU

PREFERABLYSGLT-2i with evidence of reducing HF or CKD progression in

CVOT trials if eGFR adequate------------------------------OR-----------------------------

If SGLT2i not tolerated or contraindicated or if eGFR less than adequate add GLP-1 RA with proven CVD benefit*

*Proven CVD benefit means has a label indication of reducing CVD events.

“The strategies of audit and feedback andeducational outreach visits were generally effective in improving both process of care and clinical outcomes...multifaceted interventions appeared to be more effective. ”

Chan W, et al. Circulation. 2017.

A health-system engagement strategy that will:

• Provide audit/feedbackthrough monthly, live interactions to mentor health teams in design, measurement, and monitoring of local quality improvement action plans

• Provide educational outreach with specialized quality improvement (QI) training

How to Implement Health System QI Engagement?

Central Role of Improving Evidenced-based Treatments

Best practices dashboard

Toolbox

Measurement and Feedback

Patient levelHospital level

Medications and doses

Lifestyle, diet, exercise

Monitoring and communication

↑ Survival↓ Hospitalization

Approaches Intermediate Measures Primary Outcome

• Interdisciplinary team• System for risk assessment for patient-

centered care• Telehealth vs clinical

• System for• Patient education (teach-back), focus on

medications, follow-up plan

• Call-back (to affirm plan of care)

• Come-back (to health care provider)

• System for medication reconciliation and adherence enhancement

Leveraging Systems of Care

Teach Back

Call Back

Come Back

Support TechnologyWhat’s New?

Patient Driven

• Behavior apps

• Digitally linked monitoring (Glucose, weight)

• Activity measures

• Diet monitors

Health System Driven

• Clinical reports• Health Portals• “BPAs” (best practice)• “PDAs” (decision aids)

Home-based Care for Managing Chronic Conditions

New Models of CareHome-based Care Solution

On DemandPatients access care when they need it and without

delay

Lower CostReduces financial barriers

to care for high-risk patients

$

Improved Experience

Diagnosis + treatment without leaving your home

C

The Cost of Not Taking Your MedicineBy Jane E. Brody

“There is an out-of-control epidemic in theUnited States that costs more and affects morepeople than any disease Americans currentlyworry about. It’s called nonadherence toprescribed medications, and it is—potentially,at least—100 percent preventable by the veryindividuals it afflicts.

“The numbers are staggering. ‘Studies haveconsistently shown that 20 percent to 30 percent

of medication prescriptions are never filled, and that approximately 50 percent of medicationsfor chronic disease are not taken as prescribed,’ according to a review in Annals of InternalMedicine. People who do take prescription medications—whether it’s for a simple infectionor a life-threatening condition—typically take only about half the prescribed doses.”

Brody JE. The New York Times. April 17, 2017.

Interventions Shown to Improve Adherence

• More thorough patient instructions and counseling• Pill organizers or packaging• Reminders (including telephone follow-up)• Close follow-up• Supervised self-monitoring• Rewards for success• Family or couple-focused therapy• Psychological therapy

Haynes RB, et al. Cochrane Database Syst Rev. 2008.

† 2° outcome



Each 10% improvement in ACC/AHA heart failure guideline-recommended composite care was associated with a 13% lower odds of 24-month mortality (adjusted OR 0.87; 95% CI, 0.84–0.90; P<0.0001).

Case ExampleTranslation of Evidence into Real World

Fonarow GC, et al. Circulation. 2011.

ACC/AHA Guideline-Directed Therapy for Heart Failure Improves Outcomes

• Diabetes is a growing problem with heart failure as an even worse outcome

• Prevention is the key for success

• We need to use systems of care to implement evidence faster than 17 years…our patients deserve it!

• Patients, clinicians, and systems matter

• Opportunities to improve outcomes are in everyone’s hands

• Learn what’s best on how to deliver every day!

Conclusions

• Bergenstal RM, Bailey CJ, Kendall DM. Type 2 diabetes: assessing the relative risks and benefits of glucose-lowering medications. Am J Med. 2010;123(4):374.e9–e18.

• Bertoni AG, Hundley WG, Massing MW, et al. Heart failure prevalence, incidence, and mortality in the elderly with diabetes. Diabetes Care. 2004;27(3):699–703.

• Brody JE. The cost of not taking your medicine. The New York Times. April 17, 2017;D7.

• Chan WV, Pearson TA, Bennett GC, et al. ACC/AHA special report: clinical practice guideline implementation strategies: a summary of systematic reviews by the NHLBI Implementation Science Work Group: a report of the American College of Cardiology/American Heart Association Task Force on clinical practice guidelines. Circulation. 2017;135(9):e122–e137.

• Creutzfeldt W. The incretin concept today. Diabetologia. 1979;16(2):75–85.

• Davies MJ, D'Alessio DA, Fradkin J, Kernan WN, Mathieu C, Mingrone G, Rossing P, Tsapas A, Wexler DJ, Buse JB. Management of Hyperglycemia in Type 2 Diabetes, 2018. A Consensus Report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care. 2018 Oct 4. pii: dci180033.

• DeVore AD, Cox M, Heidenreich PA, et al. Cluster-randomized trial of personalized site performance feedback in get with the guidelines—heart failure. Circ Cardiovasc Qual Outcomes. 2015;8(4):421–427.

• DeVore AD, Hammill BG, Hardy NC, et al. Has public reporting of hospital readmission rates affected patient outcomes? analysis of Medicare claims data. J Am Coll Cardiol. 2016;67(8):963–972.

• Diabetes Control and Complications Trial Research Group; Nathan DM, Genuth S, Lachin J, et al. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993;329(14):977–986.

• Duckworth W, Abraira C, Moritz T, et al; VADT Investigators. Glucose control and vascular complications in veterans with type 2 diabetes. N Engl J Med. 2009;360(2):129–139.

• Dwyer-Lindgren L, Bertozzi-Villa A, Stubbs RW, et al. Inequalities in life expectancy among US counties, 1980 to 2014: temporal trends and key drivers. JAMA Intern Med. 2017;177(7):1003–1011.

• Emerging Risk Factors Collaboration; Sarwar N, Gao P, Seshasai SR, et al. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies [published correction appears in: Lancet. 2010;376(9745):958]. Lancet. 2010;375(9733):2215–2222.

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