beta blockers in patients with atrial fibrillation and hfref ......1- ^atrial fibrillation...
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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
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
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
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.
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?
Wang, T. J. et al. Circulation 2003;107:2920-2925
Timing and Distribution of Subjects with AF, CHF, or both (Framingham Data)
Wang, T. J. et al. Circulation 2003;107:2920-2925
Unadjusted cumulative incidence of first CHF in individuals with AF (Framingham data)
Wang, T. J. et al. Circulation 2003;107:2920-2925
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
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"
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
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
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
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 (%
)
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
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
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
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
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
0,70
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
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). "
Rienstra M et al JACC-HF 2013; 1:21-28
No Evidence that Approved Heart Failure b-Blockers Lower Mortality in AF/HFREF
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)
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
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
Kotecha D et al JACC, 2017; 69:2885-96
Kotecha D et al JACC, 2017; 69:2885-96
Baseline Heart Rate and All-cause Mortality
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
0,70
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
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
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
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
0,00
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
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)
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)
0,00
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)
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%
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.