beta blockers in patients with atrial fibrillation and hfref ......1- ^atrial fibrillation...

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

Disclosures

• Employee: Advocate Heart Institute

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

• Research Grants to the Advocate Heart Institute: Abbott

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

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

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.

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?

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

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

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

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

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

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"

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 6 12 18 24 30 36 42 48

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

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

Group 1 (Post-NAF) (C)

Group 2 (No NAF) (A)

Baseline/Chronic AF (B)

Group1 (Pre-NAF) (D)

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

Rhythm Management in Patients with HF & AF

What do the Guidelines tell us?

Not much

What does the literature tell us?

Not much

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

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

Rhythm control

Months

Rate control

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

Treatment Guidelines Antiarrhythmic Choices in AF with HF

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

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)

DIAMOND Time to All-Cause Hospitalization

Dofetilide (125 patients)

Placebo (156 patients)

0 12 24 36

Time (Months)

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

ANDROMEDA Dronedarone Increases All-cause Death in HF

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

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

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

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

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

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

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

MERIT-HF (AF as AE + ECG)

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

0 6 12 18 24 30 36 42 48

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

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). "

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

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

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

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

Kotecha D. Lancet. 2014.

Sinus Rhythm Atrial Fibrillation

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

p = 0.65

CIBIS I22

US-HF28

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)

p=0.037

p=0.039

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

Baseline Heart Rate and All-cause Mortality

Kotecha D et al JACC, 2017 (in press)

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

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

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

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

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 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

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)

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

Pharmacogenetic Enhancement of Bucindolol Efficacy in Permanent AF

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

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

W8 W4 S W12 W0 W20

24-Week Follow-Up Period

Start/ECV

Drug Lead-in Period

Treatment Extension Period

Clinic Visit every 12 weeks

EOS W16 W24

Stop/1EP

Bucindolol

Metoprolol

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)

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

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)*

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

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

Weeks of Efficacy Follow-Up

Metoprolol: 70/133 (52.6%)

Bucindolol: 73/134 (54.5%)

HR = 1.01 (0.71, 1.42)

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

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)

Entire Cohort USA

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

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

HR = 0.75 (0.43, 1.32)

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

HR = 0.49 (0.24, 1.04)

MET Pro

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)

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%

USA (N=127)

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

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

HR = 0.70 (0.41, 1.19)

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

HR = 1.52 (0.68, 3.43) 0,00

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

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

HR = 0.50 (0.21, 1.21)

NED/POL/SRB (N=48)

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

Canada/Hungary (N=92)

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

Weeks of Efficacy F/U

HR = 0.83 (0.55, 1.25)

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%

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

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

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.

beta blockers in patients with atrial fibrillation and hfref ......1- ^atrial fibrillation...

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