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Beta Blockers in Patients with Atrial Fibrillation and HFrEF-Are They Truly Ineffective and, if so, Why? Maria Rosa Costanzo, M.D., F.A.H.A., F.A.C.C., F.E.S.C. Medical Director, Heart Failure Research, Advocate Heart Institute Medical Director, Edward Hospital Center for Advanced Heart Failure 801 South Washington Street Naperville, Illinois, U.S.A

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Page 1: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Beta Blockers in Patients with Atrial Fibrillation and

HFrEF-Are They Truly Ineffective and, if so, Why?

Maria Rosa Costanzo, M.D., F.A.H.A., F.A.C.C., F.E.S.C.

Medical Director, Heart Failure Research, Advocate Heart Institute

Medical Director, Edward Hospital Center for Advanced Heart Failure

801 South Washington Street

Naperville, Illinois, U.S.A

Page 2: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Disclosures

• Employee: Advocate Heart Institute

• Consultant: Respicardia, Abbott, Axon Technologies, CHF-Solutions, Fresenius

• Research Grants to the Advocate Heart Institute: Abbott

Page 3: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Prevalence of AF in the US: 10 Million by 2025

Adapted from: Miyasaka Y, et al. Circulation. 2006;114:119-25.

Projected number assuming continued increase in AF incidence rate Projected number assuming no further increase in AF incidence

Page 4: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

AF +

HF

Intersection of AF and Heart Failure

1- “Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017”, Dec 2010 2- GlobalData – “Epicast Report: Chronic Heart Failure – Epidemiology Forecast to 2022”, Jan 2013

AF AF/HF HF

2018 5.23M 2.84 (41%) 6.92M

2022 5.86M 3.09 (41%) 7.54M

Estimated Prevalence

2018: % Paroxysmal 28 Persistent 29 Permanent 53

2018: % HFrEF (<0.50) 60 HFpEF 40

Page 5: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

5

What is the impact of AF in a HFrEF patient? (Framingham, BEST trial data)

Modest increases (1.5-1.6 fold) in all-cause mortality and hospitalization burden (days in hospital/patient)1

Marked increase (by 6 fold) in hospitalization burden, after the onset1

New onset AF markedly increases HF morbidity and mortality

For this and for stroke prevention reasons AF should be aggressively prevented and if possible SR restored in HFrEF patients if it can be done safely with a reasonable chance of durability,

Permanent AF

New Onset AF

Increase (by 2 fold) in all-cause and cause specific mortality1 – Similar to 1.6 fold increase in Framingham new onset AF study in CHF2

Inference

1Aleong RG et al. Am J Med 2014; 127:963-71. 2Wang TJ et al. Circulation 2003; 107:2920.

Page 6: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

6

Any AF = 2.03 (1.79 to 2.30)

Meta-analysis of the interaction of AF on all-cause mortality in various cardiovascular diseases (Oxford and MIT)

Odutayo A et al, BMJ 354:i4482, 2016

What does AF add to ACM Risk in CV Disorders?

Page 7: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Wang, T. J. et al. Circulation 2003;107:2920-2925

Timing and Distribution of Subjects with AF, CHF, or both (Framingham Data)

Page 8: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Wang, T. J. et al. Circulation 2003;107:2920-2925

Unadjusted cumulative incidence of first CHF in individuals with AF (Framingham data)

Page 9: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Wang, T. J. et al. Circulation 2003;107:2920-2925

Unadjusted Cumulative incidence of First AF in Individuals with CHF (Framingham data)

Page 10: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Models Men, Adjusted HR (95% CI) Women, Adjusted HR

(95% CI) Co-morbid condition as a time-dependent variable (A) Mortality after AF

Impact of incident CHF 2.7 (1.9 to 3.7)* 3.1 (2.2 to 4.2)* (B) Mortality after CHF

Impact of incident AF 1.6 (1.2 to 2.1) 2.7 (2.0 to 3.6)*

Co-morbid condition as a categorical variable (C) Mortality after AF

Impact of prior CHF 2.2 (1.6 to 3.0)* 1.8 (1.3 to 2.3)* Impact of concurrent CHF‡ 2.4 (1.6 to 3.5)* 1.4 (1.0 to 1.9) (D) Mortality after CHF

Impact of prior AF 0.8 (0.6 to 1.0) 1.2 (0.9 to 1.6) Impact of concurrent AF‡ 1.0 (0.7 to 1.4) 1.1 (0.8 to 1.5)

*P≤0.0001, P<0.01.

‡Diagnosed on same day. Each letter (A through D) denotes a separate model. Models with the co-morbid condition as a time-dependent variable (A and B) are restricted to those without the co-morbid condition at the index event. Hazard ratios (HR) are adjusted for age, time period, myocardial infarction, stroke/transient ischemic attack, diabetes, valvular disease, ECG left ventricular hypertrophy, systolic blood pressure, antihypertensive therapy, and smoking.

TABLE 2. Cox Multivariable Proportional Hazards Models Examining the Impact of the Co-morbid Condition on Mortality

Wang, T. J. et al. Circulation 2003;107:2920-2925

Mortality Effect of New Onset AF or CHF as a Co-morbid Condition "We found that the development of new AF in individuals with CHF was associated with increased mortality"

Page 11: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Number at Risk:

Group 1: 190 123 92 60 44 22 5 2 0

Group 2: 2202 2049 1678 1337 1089 766 472 200 39

Group 3: 303 274 236 172 138 100 55 24 4

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,80

0,90

1,00

0 6 12 18 24 30 36 42 48

Pro

bab

ilit

y o

f E

ven

t-F

ree S

urv

ival

Months of Follow-up

Group 1 (New onset AF)

Group 2 (No AF)

Baseline/chronic group

New onset AF vs. No NAF:

HR = 2.03 (1.57 , 2.61)

Bsl/chronic vs. No AF:

HR = 1.56 (1.27 , 1.92)

P-value = 0.00002

All-Cause Mortality after New Onset AF (Group 1), Compared to No AF (Group 2) and Chronic/Established AF (HFrEF, BEST trial)

Aleong RG et al. Am J Med 127:963-71, 2014

Page 12: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Hospitalization Burden in New Onset (NAF) or Chronic AF (Baseline/Chronic),vs. BEST Patients Remaining AF Free (No NAF)

0

10

20

30

40

50

60

He

art

Failu

re H

osp

ital

izat

ion

Day

s/P

T/1

2 m

os 60

50

40

30

20

10

0

All

Cau

se H

osp

ital

izat

ion

day

s/P

T/1

2 m

os

Group 1 (Post-NAF) (C)

Group 2 (No NAF) (A)

Baseline/Chronic AF (B)

Group1 (Pre-NAF) (D)

Group

//

Aleong RG et al. Am J Med 127:963-71, 2014

*P <0.0001 vs. Group 2 †p <0.0.001 vs. Pre-NAF ‡p <0.001 vs. Baseline/Chronic §p = 0.011 vs. Group 2 ¶p <0.0002 vs. Group 2 p = 0.096 vs. Group 2 *,†, ‡

§

*,†, ‡

All-Cause HF

A

A

B

B

C

C

D

D

Page 13: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Rhythm Management in Patients with HF & AF

What do the Guidelines tell us?

Not much

What does the literature tell us?

Not much

Page 14: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Roy D et al. N Engl J Med 2008;358:2667-77

AF-CHF Trial Results

CV Death

182 v 175

p = 0.59

0 12 24 36 48 60

0

20

40

60

80

100

Even

t-fr

ee s

urv

iva

l ra

te (

%)

Rhythm control

(82% received amiodarone)

Rate control (7% received amiodarone)

Months of follow-up

HzR (Rhythm/Rate = 1.06 (0.86, 1.30)

24 36 48 60

p=0.59

Months of follow-up 0 0

12 24 36 48 60

20

40

60

80

100

Rhythm control

Months

Rate control

Worsening HF HR = 0.87 (95% CI: 0.72 - 1.06) P = 0.17

Even

t-fr

ee s

urv

iva

l (%

)

Page 15: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Treatment Guidelines Antiarrhythmic Choices in AF with HF

J Am Coll Cardiol. 2006;48(4):854-906.

Page 16: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

The Most Widely Used (Off-Label) Anti-Arrhythmic Agent to Prevent Atrial Fibrillation Is Amiodarone, which

Increases Mortality in Class II-IV HFrEF

● COMET: (Torp-Pederson C. J Cardiac Fail 2005;13:340-5)

– 50% increase in mortality in Class II-IV pts receiving amiodarone

multivariable analysis HR = 1.5 (95% C.I. 1.2,1.7), p<.001 – mortality is from circulatory failure (CF), not SD: CF HR = 2.4 (1.9,3.1), p <0.001

SD HR = 1.07 (0.8,1.4), p = 0.7

● SCD-HeFT (Bardy GH. 2005; NEJM 352:225-37)

– Class III HF, amiodarone vs. placebo ACM: n = 497; HR = 1.44 (97.5% C.I. 1.05,1.97)

Page 17: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

DIAMOND Time to All-Cause Hospitalization

Eve

nt-

fre

e P

rob

ab

ility

Dofetilide (125 patients)

Placebo (156 patients)

0 12 24 36

Time (Months)

0.0

0.2

0.4

0.6

0.8

1.0

Hazard ratio = 0.70 [0.56 - 0.89]

p = 0.003

Pedersen OD. Circulation. 2001;104;292-6

Risk of torsade de pointe = 0.8-3.3%

Requires 3-day inpatient stay

Page 18: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

ANDROMEDA Dronedarone Increases All-cause Death in HF

Kober L. N Engl J Med. 2008;358;2678

Page 19: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

AF Ablation in Patients with LV Dysfunction (N = 81, LVEF ≤0.45; Avg. 0.35; Last F/U LVEF Avg = 56.5 (Hamburg, DE))

Rillig A et al, J Cardiovasc Electrophysiol 2015; 26:1169-79

Success rate = 35%; (21 deaths) Success rate = 56%

Single Procedure

Multiple Procedures

Page 20: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Adjusted HR (95% CI) p-value

Baseline digoxin

All-cause death 1.17 (1.04, 1.32) 0.0093

Vascular death 1.19 (1.03, 1.39) 0.0201

Sudden death 1.36 (1.08, 1.70) 0.0076

All-cause hospitalization 1.02 (0.95, 1.10) 0.64

Inverse probability weighting

All-cause death 1.14 (1.01, 1.29) 0.0402

Vascular death 1.16 (1.00, 1.36) 0.0502

Sudden death 1.32 (1.06, 1.66) 0.0156

All-cause hospitalization 1.00 (0.93, 1.08) 0.94

Time varying digoxin

All-cause death 1.22 (1.08, 1.37) 0.0011

Vascular death 1.22 (1.05, 1.42) 0.0076

Sudden death 1.29 (1.03, 1.61) 0.0266

All-cause hospitalization 1.04 (0.97, 1.12) 0.30

Adjusted Outcomes w/Digoxin Use in AF (ROCKET-AF Trial, Digoxin vs. No Digoxin)

0.5 1 2

Washam J, et al. Lancet. 2015; 385:2363-70

Page 21: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Abi Nasr I et al, EHJ 2007; 28: 457–462.

Meta-Analysis of Atrial Fibrillation Prevention in b-Blocker Heart Failure Trials

Page 22: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

MERIT-HF (AF as AE + ECG)

van Veldhuisen D J et al. Eur J Heart Fail 2006; 8:539-546

0,70

0,75

0,80

0,85

0,90

0,95

1,00

0 6 12 18 24 30 36 42 48

Pro

bab

ility

of

Eve

nt-

Fre

e S

urv

ival

Months After Randomization

Placebo

Bucindolol

HR = 0.59 (0.44 – 0.79) P-value = 0.0004 Bucindolol = 75/1202 (6.2%) Placebo = 115/1190 (9.7%)

Risk reduction 41%

BEST (AF as AE + ECG)

HR = 0.52 (0.37 – 0.75) P-value = 0.0004 Metoprolol = 47/1569 (3.0%) Placebo = 85/1563 (5.4%)

Risk reduction 48%

Effect of b-blockers on Prevention of New Onset AF in Heart Failure Mortality Trials

Page 23: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

23

No approved heart failure b-blocker has shown efficacy for reducing major morbidity and mortality in HFREF patients with permanent AF (Rienstra M et al, JACC-HF 1:21-28, 2013)

JACC: Heart Failure 2013: 1:29-30

"However, all is not so sanguine at the

intersection of AF and HFREF, which occurs commonly (5) due to overlap in their underlying pathophysiologies (6). "

Page 24: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Rienstra M et al JACC-HF 2013; 1:21-28

No Evidence that Approved Heart Failure b-Blockers Lower Mortality in AF/HFREF

Page 25: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

van Veldhuisen D J et al. Eur J Heart Fail 2006;8:539-546 © 2006 European Society of Cardiology

No Evidence of Treatment Benefit for Patients in AF in MERIT-HF (Unadjusted Analysis)

Page 26: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

β blockers May Not Improve Prognosis in Patients with Concomitant HF and AF

Kotecha D. Lancet. 2014.

Sinus Rhythm Atrial Fibrillation

Page 27: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

b-blockers Do Not Decrease HF Endpoints in HFrEF Patients in “Permanent” AF (Exception is Bucindolol in b1389 Arg/Arg genotype)

0 0.25 0.5 1.0 2.0 4.0

Adapted from Kotecha D et al, Lancet 2014 and Kao D et al, EJHF 2013.

Favors β blocker Favors placebo

HR (95% CI) Weight

ACM

ACM = all cause mortality HFH = heart failure hospitalization CVM = cardiovascular mortality CVH = cardiovascular hospitalization

p = 0.65

MDC25

CIBIS I22

US-HF28

ANZ18

CIBIS II23

MERIT-HF26

COPERNICUS24

CAPRICORN20

BEST19

SENIORS27

Overall (l2=0%, p=0.65)

BEST β1389 Arg/Arg, ACM/HFH

BEST β1389 Arg/Arg, CVM/CVH

1.00 (0.34-2.95)

1.14 (0.46-2.83)

1.14 (0.56-2.32)

0.28 (0.05-1.63)

0.98 (0.64-1.51)

1.03 (0.65-1.64)

0.91 (0.54-1.54)

0.90 (0.46-1.75)

0.76 (0.54-1.06)

1.14 (0.81-1.62)

0.95 (0.81-1.12)

0.23 (0.05-1.04)

0.28 (0.08-1.01)

2.3%

3.2%

5.3%

0.8%

14.4%

12.4%

9.8%

6.0%

23.4%

22.4%

p=0.037

p=0.039

Page 28: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Kotecha D et al JACC, 2017; 69:2885-96

Page 29: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Kotecha D et al JACC, 2017; 69:2885-96

Baseline Heart Rate and All-cause Mortality

Page 30: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Baseline Heart Rate and All-cause Mortality

Kotecha D et al JACC, 2017 (in press)

Page 31: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Heart Rate Measured at the Interim Visit and All-Cause Mortality for Patients Assigned to Placebo or Beta-Blocker.

Kotecha D et al. JACC, 2017; 69:2885-96

Page 32: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Heart rate measured at the interim visit and all-cause mortality for patients assigned to placebo or beta-blocker.

Kotecha D et al. JACC, 2017; 69: 2885-96

Page 33: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Why Are Beta Blockers Ineffective in HFrEF with AF?

• Patients are older

• Patients have longer duration of HF

• In AF BB act on the AVN, where 50% of BAR are β2; Non-Selective BB may be more effective

• Patients have higher adrenergic drive, as suggested by higher NE levels

• Meta-analyses showing ineffectiveness of BB in HFrEF with AF did not include the BEST and COPERNICUS Trials

Page 34: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

β1 Adrenergic Receptor Polymorphism-Dependent Differences

Mason DA et al. JBC 1999; Taylor et al. Cong Heart Fail 2004; Liggett et al. PNAS 2006; Walsh et al. J Card Fail 2008; O'Connor et al. PLOS ONE, 2012.

b1389Arg >>> b1389Gly Binding affinity for norepinephrine Signal transduction capacity Constitutively active receptors

C G nt 1165 Arg Gly 389

Frequency = EA 0.52, AA 0.32

Bucindolol has two unique properties that are specific for 389Arg b1-ARs: − Sympatholysis – Inverse Agonism

Page 35: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Interaction p = 0.008

Kaplan-Meier curves for prevention of atrial fibrillation in BEST: DNA substudy (Aleong et al, JACC Heart Fail; 1:338-44, 2013)

BEST DNA Sub-study: Prevention of Atrial Fibrillation by Bucindolol

0,70

0,75

0,80

0,85

0,90

0,95

1,00

0 6 12 18 24 30 36 42 48Months After Randomization

b1389 Arg/Arg (n = 441; 36 events)

HzR = 0.26 (0.12 – 0.57) P-value = 0.0003

BUC

PLB

0,70

0,75

0,80

0,85

0,90

0,95

1,00

0 6 12 18 24 30 36 42 48Months After Randomization

HzR = 1.01 (0.56 – 1.84) P-value = 0.97

b1389 Gly Carriers (n = 484; 44 events)

BUC

PLB

Aleong et al, JACC Heart Fail; 1:338-44, 2013

Page 36: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Pharmacogenetic Enhancement of Bucindolol Efficacy in Permanent AF

Kao DP et al, Eur J Heart Fail 2013; 15:324-33

Page 37: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

GENETIC-AF

Phase II Trial of Pharmacogenetic Guided Beta-Blocker Therapy with Bucindolol vs. Metoprolol for the Prevention of Atrial

Fibrillation/Flutter in Heart Failure

Page 38: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

W8 W4 S W12 W0 W20

24-Week Follow-Up Period

Start/ECV

R

Drug Lead-in Period

Treatment Extension Period

Clinic Visit every 12 weeks

EOS W16 W24

Stop/1EP

Bucindolol

Metoprolol

W2

8-week Screening

Period

Medtronic device (if needed) inserted any time between Randomization and Week 0

Genotype

GENETIC-AF Study Design • Phase 2B 3 Seamless Design • Phase 2 interim analysis (230 pts) • Bayesian predicted probability of success (PPoS)

1. PPoS < 0.10 (Futility, stop study) 2. 0.10 ≤ PPoS < 0.40 (Complete Phase 2) 3. PPoS ≥ 0.40 (Seamless transition to Phase 3)

Rand

Page 39: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Key Eligibility Criteria

1. History of HF with reduced left ventricle ejection fraction (HFrEF + HFmrEF)

• LVEF < 0.50 within 12 months of the Screening Visit

• Excluded: NYHA class IV

• Excluded: Significant fluid overload at Randomization

2. Symptomatic paroxysmal or persistent AF episode ≤ 180 days of Screening Visit

• Excluded: Permanent AF > 1 year

3. Possess the β1389Arg/Arg (ADRB1 Arg389Arg) genotype

4. Receiving appropriate anticoagulation therapy prior to randomization for stroke

5. Clinically appropriate for ECV if AF/AFL is present at the Week 0 Visit

• Excluded: More than 2 ECVs within 6 months of Randomization

• Excluded: Most recent ECV failed to produce sinus rhythm

6. Systolic BP > 90 mmHg and < 150 mmHg at Randomization

7. Heart rate ≥ 60 bpm (if BB naïve) and < 180 bpm (all) at Randomization

Page 40: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Baseline Characteristics (± SD; *p <0.05 vs. MET)

Parameter MET

n = 133 BUC

N = 134

Age 65.5 ± 10.0 65.8 ± 10.3

Gender M/F (%) 81 / 19 83 / 17

LVEF 0.36 ± 0.10 0.36 ± 0.10

NYHA I / II / III (%) 26 / 54 /20 30 / 60 / 10

Hx Ischemic / Non-Ischemic HF (%) 33 / 67 31 / 69

Randomized in AF / Not in AF (%) 52 / 48 49 / 51

Hx Persistent/Paroxysmal AF (%) 51 / 49 51 / 49

AF Dx to Randomization, days 1180 ± 2209 1431 ± 2271

HF Dx to randomization, days 1054 ± 1733 1252 ± 2070

sBP (mm Hg) 122 ± 15.7 125 ± 14.9

Heart Rate, bpm 76.0 ± 17.7 76.5 ± 17.9

Previous ECV / AF ablation / Class III AADs (%) 50 / 20 / 46 49 / 21 / 50

Device Type: ILR / CRT / ICD / PM (%) 15 / 10 / 12 / 10 17 / 6 / 18 / 9

HF Rx: b-bl / ACEI or ARB / Dig / Diuretic / MRA / Scbtl-Val (%) 92 / 78 / 17 / 61 / 32 / 5 94 / 75 / 15 / 57 / 32/ 4

NT-proBNP (pg/ml) 1343 ± 1846 1159 ± 1306

Norepinephrine (NE) (pg/ml) 664 ± 359 682 ± 348

Change in NE at Week 4, median (Q1, Q3) -10 (198, 121) -101 (-241, 43)*

Page 41: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Primary Endpoint: Time to First AF/AFL/ACM Event

0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,80

0,90

1,00

0 2 4 6 8 10 12 14 16 18 20 22 24 26

Pro

ba

bilit

y o

f N

o A

F/A

FL

/AC

M

Weeks of Efficacy Follow-Up

Metoprolol: 70/133 (52.6%)

Bucindolol: 73/134 (54.5%)

HR = 1.01 (0.71, 1.42)

BUC

MET

0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,80

0,90

1,00

0 2 4 6 8 10 12 14 16 18 20 22 24 26

Pro

ba

bilit

y o

f N

o A

F/A

FL

/AC

M

Weeks of Efficacy Follow-Up

Metoprolol: 40/67 (60%)

Bucindolol: 33/60 (55%)

HR = 0.70 (0.41, 1.19)

Unadjusted HR: Entire Cohort = 0.96 (95% CI: 0.69, 1.33); U.S. Cohort = 0.77 (95% CI: 0.48, 1.22)

BUC

MET

Entire Cohort USA

Page 42: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Time to First AF/AFL/ACM Event: AF Burden Substudy AF Event = AFB ≥ 6 hours/day

0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,80

0,90

1,00

0 2 4 6 8 10 12 14 16 18 20 22 24 26Weeks of Efficacy Follow-Up

Metoprolol: 25/34 (74%)

Bucindolol: 24/35 (69%)

HR = 0.75 (0.43, 1.32)

BUC

MET

0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,80

0,90

1,00

0 2 4 6 8 10 12 14 16 18 20 22 24 26Weeks of Efficacy Follow-Up

Metoprolol: 18/23 (78%)

Bucindolol: 12/19 (63%)

HR = 0.49 (0.24, 1.04)

Pro

bab

ility

of

No

AF/

AFL

/AC

M

BUC

MET Pro

bab

ility

of

No

AF/

AFL

/AC

M Entire Cohort USA

Adjusted HR: Entire Cohort = 0.74 (95% CI: 0.38, 1.45); U.S. Cohort = 0.50 (95% CI: 0.17, 1.42)

Page 43: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

AEs, Hospitalization, Stroke or Death

Endpoint Metoprolol

(N=133)

Bucindolol

(N=134)

AEs leading to permanent study drug discontinuation 8.3% 8.2%

AEs leading to study withdrawal (excluding death) 1.5% 1.5%

AEs: Bradycardia 12.0% 3.7%

AEs: Stroke (99% on OACs) 0.0% 0.0%

SAEs: Any cardiovascular event 9.8% 9.0%

All-cause hospitalization 15.0% 20.1%

Cardiovascular hospitalization 10.5% 12.7%

Heart failure hospitalization 7.5% 6.7%

All-cause mortality 2.3% 2.3%

Cardiovascular mortality 1.5% 0.7%

Heart failure mortality 0.7% 0.0%

Page 44: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

USA (N=127)

Canada (N=59) Hungary (N=33)

0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,80

0,90

1,00

0 2 4 6 8 10 12 14 16 18 20 22 24 26

HR = 0.70 (0.41, 1.19)

0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,80

0,90

1,00

0 2 4 6 8 10 12 14 16 18 20 22 24 26

HR = 1.52 (0.68, 3.43) 0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,80

0,90

1,00

0 2 4 6 8 10 12 14 16 18 20 22 24 26

HR = 2.90 (0.71, 11.8)

Time to First AF/AFL/ACM Event by Region

BUC

MET

BUC

MET

BUC

MET

0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,80

0,90

1,00

0 2 4 6 8 10 12 14 16 18 20 22 24 26

HR = 0.50 (0.21, 1.21)

BUC

MET

NED/POL/SRB (N=48)

Pro

ba

bil

ity o

f N

o A

F/A

FL

/AC

M

Pro

ba

bil

ity o

f N

o A

F/A

FL

/AC

M

Pro

ba

bil

ity o

f N

o A

F/A

FL

/AC

M

Pro

ba

bil

ity o

f N

o A

F/A

FL

/AC

M

USA/NED/POL/SRB (N=175)

Canada/Hungary (N=92)

Page 45: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Time to First AF/AFL/ACM Event LVEF < 0.39 (median) or LVEF 0.39-0.49 with

HF Dx to Rand AF Dx to Rand (DTRI) >-30 days

0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,80

0,90

1,00

0 2 4 6 8 10 12 14 16 18 20 22 24 26

Pro

ba

bil

ity o

f N

o A

F/A

FL

/AC

M

Weeks of Efficacy F/U

Metoprolol: 55/98 (56%)

Bucindolol: 56/107 (52%)

HR = 0.83 (0.55, 1.25)

BUC

MET

Unadjusted HR: Entire Cohort = 0.84 (95% CI: 0.58, 1.22)

Country Included (%)

All 77%

USA 85%

Canada 78%

Hungary 39%

Poland 78%

Serbia 81%

Netherlands 75%

Page 46: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

GENETIC-AF Conclusions

• Pharmacogenetic guided bucindolol did not reduce AF/AFL/ACM recurrence compared to the active comparator metoprolol in the overall population

• Trends for bucindolol benefit were observed in several large subpopulations

• Bucindolol appears to have a similar safety profile compared to metoprolol

• These Phase 2 results merit further investigation in a redefined population

HFmrEF (LVEF ≥0.40 and <0.50) if DTRI > -30 days

HFrEF (LVEF < 0.40)

Symptomatic paroxysmal/persistent AF ≤ 180 days of randomization

β1389Arg/Arg genotype

Page 47: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

OVERALL CONCLUSIONS • New Onset AF worsens HF mortality

• New Onset AF predicts HF progression

• BB are effective in preventing AF in HF regardless of baseline risk • Prevention or improvement of LV remodeling • Attenuation of SNS activity • Prevention of atrial ischemia on HF due to IHD

• In contrast to their effects in HFrEF patients in SR, BB do not decrease HF hospitalization and mortality in patients with HFrEF and AF: • BB act on SN in SR Vs. AVN in AF • Due to loss of “atrial kick” HF patients with AF may need higher HR

for hemodynamic stability • Low HR may indicate underlying conduction abnormalities • In HF, AF may be a marker of more severe and less modifiable

disease

Page 48: Beta Blockers in Patients with Atrial Fibrillation and HFrEF ......1- ^Atrial Fibrillation Therapeutics – Pipeline Assessment and Market Forecasts to 2017 _, Dec 2010 2- GlobalData

Conclusions cont’d • In contrast to SR, neither HR change from baseline nor

attained HR are associated with outcomes in HFrEF with AF

• In contrast to other BB, bucindolol improved outcomes in advanced HFrEF patients who achieved a HR ≤ 80 bpm

• The effects of bucindolol are linked to the presence of β1 389 Arg/Arg genotype

• In this genotype, the 73% reduction in new onset AF s much higher than that occurring with other BB

• After GENETIC-AF, the effects of bucindolol merit further investigation in well defined patient populations.