HFpEF 2016 : Comorbidities and Outcomes

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HFpEF 2016 : Comorbidities and Outcomes Christopher M. O Connor, MD, FACC CEO and Executive Director, Inova Heart and Vascular Institute Professor of Medicine, Duke University Editor in Chief, JACC: Heart Failure President-Elect HFSA

DISCLOSURES Dr. O Connor receives or has received research support and consulted for Bayer, Merck, Medtronic, Boston Scientific, ResMed, BMS, and NHLBI.

HFpEF Prevalent Disease High morbidity and cost to society No specific therapy beyond symptom reduction that is recommended or approved

Systolic Heart Failure Normal Diastolic Heart Failure Aurigemma, Zile, Gaasch Circulation 2005

Progress in HFpEF Heterogeneity and pathophysiology Mid range LV ejection fraction (HFmrEF) Comorbidities Treatment

Annual Event Rate (per 1000 pts) EF 40 % EF 40-50 % EF 50 % HFPEF: Half of Heart Failure, Similar Signs and Symptoms and Increasing in Prevalence OPTIMIZE-HF Registry, N=41,267 % 35 Reduced 30 Preserved 25 20 15 10 5 Fonarow G et al. JACC. 2007; 50:768-777. 0 Edema PND Rest dyspnea S 3 Crackles JVP >6 cm Orthopnea Cardiomegaly CHARM Investigators 12 10 8 6 4 White Men Black Men White Women Black Women 2 0 2005 2007 2009 2011

Why Prior HFpEF Trials have Not Been Successful Wrong Patients Comorbidities Wrong Endpoints No Disease Wrong Therapies

European heart Journal:published online: 20 May 2016

The middle child in heart failure: heart failure with mid-range ejection fraction (40 50%) European Journal of Heart Failure (2014) 16, 1049 1055 Annals of internal medicine 2002; 137:631-639

Heterogeneity of the heart failure with preserved ejection fraction syndrome.

A high degree of disease heterogeneity exists within heart failure patients and there is a need for improved phenotyping of the syndrome A new taxonomy of heart failure based on both clinical and molecular measures may provide a more accurate classification of disease and ultimately enhance diagnosis and treatment

Cluster Analysis Cluster analysis is an unsupervised learning task of grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups J Am Coll Cardiol. 2014;64:1765-74

Cluster Analysis of Heart Failure to Uncover Distinct Phenotypes? Circulation. 2014; Nov 14

Implications of Co-Morbidities Increase heterogeneity Complicates management(beta agonists;nsaid) Associated with worse outcomes Increase in non-cardiac outcomes Mentz RJ and Felker GM. Heart Fail Clin 2013

Real Disease or Just a Collection of Comorbidities? HFrEF HFpEF P-value Age 71.8 ± 12 75.4 ± 11.5 < 0.001 70 60 Hypertension 49.2% 55.1% 0.005 Atrial Fibrillation 23.6% 31.8% < 0.001 COPD 13.2% 17.7% 0.002 50 40 30 20 10 0 Mortality HF Hosp Anemia 9.9% 21.1% < 0.001 Bhatia et al. NEJM 2006

Comorbidities drive myocardial dysfunction and remodeling in HF PEF

Bidirectional Impact Mentz RJ, O Connor CM et al. JACC 2014

Wrong Therapies?: Outcomes Trials in HFpEF CHARM-Preserved PEP-CHF I-PRESERVE TOPCAT

RAS Inhibitors in HFpEF Marginal Effect OR (95% CI) % Weight Primary Event TOPCAT CHARM-Preserved I-PRESERVE PEP-CHF Overall 0.89 (0.75, 1.06) 0.88 (0.74, 1.04) 0.95 (0.84, 1.08) 0.92 (0.67, 1.26) 0.92 (0.84, 1.00) 24.66 24.53 43.65 7.15 100.00 P = 0.043 Primary Event P = 0.053 CV Death or HHF.673 1 1.49

2016 ESC Guidelines No treatment has yet been shown, convincingly, to reduce morbidity and mortality in patients with HF- PEF.

TOPCAT : Primary Outcome (CV Death, HF Hosp, or Resuscitated Cardiac Arrest) 351/1723 (20.4%) Placebo Spironolactone HR = 0.89 (0.77 1.04) p=0.138 320/1722 (18.6%)

Wrong Patients?: TOPCAT: Results by Region US, Canada, Argentina, Brazil HR=0.82 (0.69-0.98) Placebo: 280/881 (31.8%) Interaction p=0.122 Placebo: 71/842 (8.4%) Russia, Rep Georgia HR=1.10 (0.79-1.51) Pfeffer MA et al. Circulation. 2015 Jan 6;131(1):34-42

TOPCAT: WHY Many patients in Russian and Georgia did not have a rise in potassium with spironolactone (Pfeffer et al. Circulation 2015) Canrenone, a spironolactone metabolite, not elevated in many patients in Russia and Georgia (O Meara et al. HFSA 2016) These data suggest that these patients were likely NOT taking study drug!

Wrong Endpoints? Time to first event analysis may not capture the full burden of disease and throws out many informative endpoints after the first Perhaps utilizing recurrent non-fatal events can improve our power, reduce sample size, and better capture the burden of disease 24

Example: CHARM-Preserved HF Hospitalisations Candesartan (N=1513) Placebo (N=1508) 1 Admission 229 278 2 Admissions 94 114 All Admissions 390 547 Unused Admissions 126 269 Rate Ratios for Composite of Recurrent Heart Failure Hospitalisations and Cardiovascular Death Joint Frailty Model HR 95% CI P-value Poisson 0.78 (0.69,0.87) <0.001 Negative Binomial 0.75 (0.62,0.91) 0.003 Andersen-Gill (robust SE) 0.78 (0.65,0.93) 0.006 Rate ratio 0.69 (0.55,0.85) <0.001 Rogers et al. Eur J Heart Fail 2014

Promising Therapies

NEAT-HFpEF:Isosorbide Mononitrate in Heart Failure with Preserved Ejection Fraction (LVEF>50%) NEJM 2016: 373:2314-24

Nitrites in HFpEF acute infusion of inorganic nitrite on exercise hemodynamics Inhaled sodium nitrite hemodynamics Circulation. 2016;134:73-90 Circ Res 2016;119:880-886

SDB prevalence in HFpEF Bitter et al., Eur J Heart Fail 2009

CAT-HF Study Objectives Evaluate the effect of minute ventilation-targeted adaptive servoventilation (ASV) in acute decompensated heart failure (HF) patients on outcomes at 6 months. Primary Outcome Global Rank Endpoint: Rank order response based on survival free from CV hospitalization and improvement in functional capacity measured by 6MWD Key Secondary Outcomes CV and all-cause death SDB parameters Change in 6MWD

CAT-HF Prespecified Analysis: Primary Endpoint HFpEF HR (95%CI) Cox p-value Global rank endpoint 0.36 (0.14, 0.93) 0.036

Implantable Hemodynamic Monitoring System mmhg Furosemide 160mg BID Metolazone 5mg QD Metolazone 2.5mg QD E A B C D

Cumulative Number of HF Hospitalizations Cumulative HF Hospitalizations Over Entire Randomized Follow-Up Period 260 240 Treatment Control 220 200 p < 0.001, based on Negative Binomial Regression 180 160 140 120 100 80 60 40 20 6 Months 15 Months 0 0 90 180 270 360 450 540 630 720 810 900 At Risk Treatment 270 262 244 209 168 130 107 81 28 5 1 Control 280 267 252 215 179 138 105 67 25 10 0 Days from Implant

Kaplan-Meier Estimate of Cumulative Rates (%) Kaplan-Meier Estimate of Cumulative Rates (%) Kaplan-Meier Estimate of Cumulative Rates (%) PARADIGM-HF Primary Results Significant Reduction in Primary Endpoints, CV Death and All-Cause Mortality 32 24 16 Patients at Risk LCZ696 Enalapril 8 0 Enalapril (n=4212) LCZ696 (n=4187) HR = 0.80 (0.73-0.87) P = 0.0000004 Number needed to treat = 21 0 180 360 540 720 900 1080 1260 4187 4212 3922 3883 Days After Randomization 3663 3579 3018 2922 2257 2123 1544 1488 896 853 249 236 1117 914 LCZ696 Enalapril 32 24 16 Patients at Risk 8 4187 4212 HR = 0.80 (0.71-0.89) P = 0.00008 Number need to treat = 32 4056 4051 Days After Randomization 3891 3860 3282 3231 2478 2410 Enalapril (n=4212) 1716 1726 LCZ696 (n=4187) 0 0 180 360 540 720 900 1080 1260 1005 994 280 279 693 558 32 24 HR = 0.84 (0.76-0.93) P<0.0001 Enalapril (n=4212) 835 711 16 8 LCZ696 (n=4187) Patients at Risk LCZ696 Enalapril 0 0 180 360 540 720 900 1080 1260 4187 4212 4056 4051 Days After Randomization 3891 3860 3282 3231 2478 2410 1716 1726 1005 994 280 279

Percent of Patients NTproBNP (pg/ml) Change in Left Atrial Volume (ml) PARAMOUNT: Significant Improvement in Several Domains Improvement in NT-proBNP Left Atrial Volume Improvement in Left Atrial Size 1000 900 800 862 (733,1012) 835 (710, 981) Valsartan 2 1 0 12 Weeks 36 Weeks 700 600 500 400 300 200 783 (670,914) p = 0.063 0 5 10 12 Weeks Post Randomization LCZ696 LCZ696/Valsartan: 0.77 (0.64, 0.92) P = 0.005 605 (512, 714) 110 100 90 80 70 60 50 40 30 20 10 0 Improvement in NYHA Class Worsened Unchanged Improved P = 0.11 P = 0.05 LCZ696 Valsartan -1-2 -3-4 -5-6 LCZ696 Valsartan Week 12 Week 36 P = 0.18 P = 0.003 LCZ696 Valsartan Solomon et al. Lancet 2012

PARAGON-HF: study design Target patient population: 4,600 patients with symptomatic HF (NYHA Class II IV) and LVEF 45%, Structural Heart Disease, and Natriuretic Peptide Elevation Randomization 1:1 Active run-in period Double-blind treatment period LCZ696 200 mg BID Screening Valsartan 80 mg BID* LCZ696 100 mg BID Valsartan 160 mg BID On top of optimal background medications for comorbidities (excluding ACEIs and ARBs) up to 2 weeks 3 8 weeks ~240 weeks Primary outcome: CV death and total (first and recurrent) HF hospitalizations (anticipated ~1,721 primary events)

PARAGON-HF Current Status 11,024 patients screened 4309 patients currently randomized 223 patients in screening (success rate 54%) and 396 patients in run-in (success rate ~84%) All screening activities will cease prior to holidays 2016! LPLV expected in March 2019, FIR July 2019

INfluenza Vaccine to Effectively Stop CardioThoracic Events and Decompensated Heart Failure in Patients with CVD (INVESTED) N = 9300 total patients up to 3 yrs exposure Post-MI or HF Hospitalization ~16,000 pt-years total exposure High Dose Trivalent Influenza Vaccine RANDOMIZED 1:1 DOUBLE BLIND ANNUAL VACCINE STRATEGY Standard Dose Quadrivalent All other CV Rx per treating MD Influenza Vaccine Duration 3 Influenza Seasons + Vanguard Season Followed up to 4 times a year with annual re-vaccination to assigned strategy Primary EP Death or Cardiopulmonary Hospitalization

The O Connor Formula Confirm Diagnosis(NT probnp,echo HFH) Identify and Treat Comorbidities Volume Management Spiro Cardio-MEMs for recurrent HFH Enroll in Clinical Trials(Paragon, Invested)

The Year in Review : HFpEF Heterogeneity and pathophysiology concepts may link to personalized medicine Mid range LV ejection fraction (HFmEF)- possible benefit from systolic heart failure therapies Comorbidities can confuse the correct diagnosis but also likely promote the development and progression of HFpEF Treatment Challenging

How Will President-Elect Trump Influence HF Care Health Care Systems will have reduced margins for uncompensated care, innovation, and expensive therapies Move to Bundle Care Initiatives will slow The threshold for evidence generation at the FDA will be less

Predictive Medicine : A New Treatment or Another Championship?