Abstract
Aims:
We sought to describe the baseline characteristics of PARALLAX (a randomized controlled trial of sacubitril/valsartan vs. individualized medical therapy in heart failure [HF] with mildly reduced and preserved ejection fraction [HFpEF]); compare PARALLAX to recent HFpEF trials; and examine the clinical characteristics associated with quality of life (QOL) and 6-minute walk distance (6MWD).
Methods and Results:
A total of 2566 patients with HF and left ventricular ejection fraction (LVEF) >40% were randomized, of whom 96% had an LVEF ≥ 45%. Multivariable linear regression was used to determine characteristics associated with Kansas City Cardiomyopathy Questionnaire clinical summary score (KCCQ-CSS) and 6MWD. Mean age was 73±8 years, 51% were female, and comorbidities were common. Of the QOL measures tested in PARALLAX, the SF-36 physical functioning score was most closely correlated with 6MWD (R=0.41, P<0.001), and outperformed the KCCQ physical limitation score (R=0.33) and KCCQ-CSS (R=0.31) on multivariable analyses. Female sex, higher body mass index (BMI), history of coronary artery disease (CAD), lower LVEF, and higher N-terminal B-type natriuretic peptide (NTproBNP) were associated with worse (lower) KCCQ-CSS; older age, female sex, higher BMI, diabetes, CAD, chronic obstructive pulmonary disease, prior HF hospitalization, lower LVEF, and higher NTproBNP were associated with shorter 6MWD (P<0.05 for all associations).
Conclusions:
PARALLAX is the largest HFpEF study to date to examine 6MWD together with QOL. The KCCQ-CSS and 6MWD were modestly correlated, and several factors were associated with worse values of both. These results provide insight into the association between QOL and exercise capacity in HFpEF.
Keywords: heart failure with preserved ejection fraction, randomized controlled trial, quality of life, exercise capacity, angiotensin receptor neprilysin inhibitor
Graphical Abstract
Summary of the PARALLAX Trial and the Relationship Between NTproBNP, 6-Minute Walk Test Distance, KCCQ, SF-36, and Heart Failure Signs and Symptoms
pts = patients; HF = heart failure; LVEF = left ventricular ejection fraction; RCT = randomized controlled trial; NTproBNP = N-terminal pro-B-type natriuretic peptide; 6MWD = 6-minute walk test distance; KCCQ = Kansas City Cardiomyopathy Questionnaire; SF-36 = Short Form Health Survey-36; ACE-I = angiotensin converting enzyme inhibitor; ARB = angiotensin receptor blocker; RASi = renin angiotensin system inhibitor; NYHA = New York Heart Association.
INTRODUCTION
In the phase 3 PARAGON-HF1 randomized controlled trial of sacubitril/valsartan vs. valsartan in patients with heart failure and preserved ejection fraction [HFpEF], change in quality of life (QOL) at 8 months, as measured by the Kansas City Cardiomyopathy Questionnaire (KCCQ) clinical summary score (CSS), was minimally better (+1.0 [95% CI 0.0–2.1] difference) in sacubitril/valsartan compared to the valsartan treated patients. However, patients enrolled in PARAGON-HF had relatively preserved QOL (mean KCCQ-CSS = 72 at baseline, which increased after the run-in phase to a mean KCCQ-CSS of 74 at randomization) compared to other clinical trials such as TOPCAT (mean baseline KCCQ-CSS = 57).2 Therefore, it is possible that patients with more symptomatic HFpEF and lower QOL could benefit to a greater extent from sacubitril/valsartan in terms of QOL.
Most contemporary large-scale, multicenter HFpEF randomized controlled trials (including PARAGON-HF) have not examined exercise capacity but instead have focused on hard endpoints such as HF hospitalization and cardiovascular (CV) death. However, exercise capacity is an important aspect of the patient journey that could be ameliorated by novel therapeutics in patients with HFpEF. For this reason, recent US Food and Drug Administration guidance states that improvement in QOL and exercise capacity (without a favorable effect on hard endpoints) are valid for approving drugs for HF, suggesting that they should be used more commonly as important endpoints in HFpEF clinical trials.3
It is for these reasons that PARALLAX (Prospective comparison of ARni versus comorbidity-Associated conventionaL therapy on QOL And eXercise capacity) was designed and conducted in patients with HF, LVEF > 40%, and KCCQ-CSS < 75, with a specific focus on QOL and exercise capacity.4 In addition, PARALLAX sought to compare sacubitril/valsartan to individualized medical therapy (based on type of renin angiotensin system [RAS] inhibitor use or lack thereof prior to randomization).
PARALLAX is the largest study to date to examine exercise capacity in HFpEF, thereby offering a unique opportunity to understand the baseline characteristics associated with reduced exercise capacity and worse QOL in patients with HFpEF. Therefore, we sought to: (1) describe the baseline characteristics of the PARALLAX study participants; (2) compare PARALLAX to recent HFpEF clinical trials; and (3) examine the factors associated with NTproBNP, QOL, and exercise capacity at baseline in the PARALLAX trial.
METHODS
PARALLAX study design and objectives
The objectives and design of the PARALLAX study have been described in detail previously.4 Briefly, PARALLAX was designed as a multi-center, international, randomized, double blind trial of sacubitril/valsartan vs. individualized medical therapy in adults with HFpEF recruited from 396 clinical sites across 32 countries. The trial was funded by Novartis. Enrollment began in August 2017 and concluded in May 2019. The primary aims of the PARALLAX study are to determine whether treatment with sacubitril/valsartan, compared to individualized medical therapy (ACE-inhibitor [enalapril], ARB [valsartan] or no RAS inhibition [placebo], depending on baseline RAS inhibitor medication use), can improve NTproBNP at 12 weeks and exercise capacity (6-minute walk test distance [6MWD]) at 24 weeks (co-primary endpoints), and QOL (KCCQ-CSS) at 24 weeks (key secondary endpoint), in patients with HF and LVEF > 40%.
The PARALLAX trial has been registered (clinicaltrials.gov identifier NCT03066804) and is in compliance with the Declaration of Helsinki. Approval from the responsible local authorities and ethics committees was obtained prior to inclusion of patients, and all patients provided written informed consent.
Selection of study patients: inclusion criteria, and exclusion criteria
Inclusion criteria for PARALLAX are as follows: age ≥ 45 years; symptomatic HF requiring the use of diuretics in the last 30 days prior to enrollment; New York Heart Association (NYHA) functional class II to IV at screening; an LVEF >40%; elevated NTproBNP levels (>220 pg/ml in sinus rhythm and >600 pg/ml in patients with atrial fibrillation or flutter [AF] at time of screening); objective evidence of structural heart disease (either left atrial enlargement or left ventricular hypertrophy) on echocardiography within 6 months prior to screening; and reduced QOL (KCCQ-CSS <75). We sought to determine whether sacubitril/valsartan is associated with improved QOL compared to individualized medical therapy. For this reason, we excluded patients with KCCQ ≥ 75 because we hypothesized that we would not be able to demonstrate improvement in QOL if the KCCQ scores were too high (reflecting good QOL) in the enrolled patients. In addition, patients on therapy with an ACE-inhibitor or ARB were required to have a history of hypertension. There were specific exclusion criteria for PARALLAX, as detailed previously.4 Importantly, patients were excluded if 6MWD was primarily limited by non-cardiac comorbid conditions or if they had an alternative reason for shortness of breath such as significant pulmonary disease or severe chronic obstructive pulmonary disease (COPD), hemoglobin <10 g/dL in males and < 9.5 g/dL in females, or body mass index (BMI) > 40 kg/m2. Supplemental Table S1 compares the inclusion/exclusion criteria of PARALLAX to other contemporary HFpEF trials that included exercise capacity and QOL endpoints.
Baseline data
Each patient enrolled in the PARALLAX study underwent a detailed baseline visit, that included medical history (based on patient self-report and chart review). The following medical history variables were collected: NYHA functional class, prior hospitalization for HF, myocardial infarction, coronary artery disease, dyslipidemia, atrial fibrillation, and diabetes mellitus. All medications were also documented at the time of the baseline study visit and at the time of randomization. Physical examination and laboratory data collected at baseline included heart rate, blood pressure, height, weight, BMI, creatinine, estimated glomerular filtration rate (GFR, calculated using the MDRD formula), and hemoglobin. All patients underwent testing for NTproBNP at the time of screening. NTproBNP was measured by a central lab using the proBNP II assay (Roche Diagnostics, Basel, Switzerland).
Quality of life and exercise capacity
The KCCQ5, 6 was administered to all PARALLAX patients. The range of possible scores on the KCCQ is 0 to 100, and lower scores indicate a worse QOL. The Short Form Health Survey (SF-36)7 was also administered as a QOL measure in PARALLAX (lower scores indicated worse QOL). All PARALLAX patients also underwent standardized 6-minute walk tests (6MWT) at baseline, according to published guidelines.8 Each site and study staff were trained on the proper conduct of the 6MWT, and 6MWD was measured on all patients who were able to undergo the 6MWT.
Statistical analysis
Baseline characteristics were summarized as counts and percentages for categorical variables and means and standard deviations (or median [25th-75th percentile] when appropriate) for continuous variables. The baseline characteristics were reported for the entire study and also by RAS-inhibitor strata (ACE-inhibitor vs. ARB vs. no RAS inhibition). We compared baseline characteristics across strata using one-way analysis of variance for continuous variables and Chi-squared tests (or Fisher exact tests, where appropriate) for categorical variables. We repeated statistical testing for comparison of the RAS-inhibitor (ACE-inhibitor plus ARB groups) vs. no RAS inhibition group using t-tests for continuous variables and Chi-squared tests (or Fisher exact tests, where appropriate) for categorical variables. Similar analyses were done for additional comparisons of baseline characteristics (LVEF 40–50% vs. > 50%; tertiles of NTproBNP, KCCQ-CSS, and 6MWD). We also created a heatmap of the correlation of NTproBNP, KCCQ scores, 6MWD, SF-36, NYHA class, and signs and symptoms of HF (with ordering of variables based on hierarchical clustering using hclust in R).
Multivariable linear regression was used to examine the association of a variety of variables with NTproBNP, KCCQ-CSS, and 6MWD at baseline. NTproBNP was log-transformed before inclusion into multivariable linear regression models as the dependent variable. The candidate variables examined for association with the 3 aforementioned “outcome” variables included age; sex; race/ethnicity; region of enrollment; RAS inhibition strata; comorbidities (obesity [BMI], hypertension [systolic blood pressure], chronic kidney disease [eGFR], anemia [hemoglobin], diabetes, atrial fibrillation or flutter, coronary artery disease, asthma, COPD, and obstructive sleep apnea [OSA]); prior HF hospitalization; NYHA class; and LVEF. NTproBNP was additionally included in the multivariable linear regression models for KCCQ-CSS and 6MWD, and KCCQ-CSS was additionally included in the multivariable regression models for 6MWD.These candidate variables were entered successively into 3 multivariable models (with the final model containing all variables/covariates). In sensitivity analyses, KCCQ-CSS was replaced with the KCCQ physical limitation score and SF-36 general health score. We also examined the effect of replacing BMI with height and weight separately in the 6MWD multivariable analyses given the known associations between shorter stature and lower 6MWD. Model comparison was performed using the Akaike information criterion and Bayesian information criterion. The beta-coefficients and 95% confidence intervals (CIs) were reported for all associations in the multivariable analyses. A two-sided p-value < 0.05 with adjustment for multiple comparisons using the false discovery rate (FDR) method (which corresponded to p < 0.025) was considered statistically significant. Analyses were done using SAS version 9.4 or higher (SAS Institute), Stata version 15.1 (StataCorp), and R version 3.5.2 (The R Foundation for Statistical Computing).
RESULTS
Enrollment of PARALLAX study participants
The first PARALLAX study patient was enrolled on August 22, 2017, and enrollment concluded on 7 May 2019 with a total of 4632 patients screened, and 2572 patients randomized, at 396 clinical sites in 32 countries. Of the 2572 randomized patients, 6 were excluded after randomization (prior to receiving any doses of study drug) due to mis-randomization or mis-stratification. The remaining 2566 patients were included in the present analysis of baseline characteristics and represent the Full Analysis Set for the PARALLAX trial. The majority of patients (75%) were enrolled in Eastern and Western Europe, and Germany was the country with the highest enrollment into the trial (n=415/2566 [16%]).
As shown in Table 1 and Figure 1, patients enrolled in PARALLAX had signs, symptoms, and objective evidence of symptomatic HF. LVEF (mean 56.5%) was in the preserved range in the majority. Of the 2566 enrolled patients, 111 (4.3%) had an LVEF in the 41–44% range. The majority of patients were NYHA class II (68%) or class III (32%); NTproBNP was elevated (median value 769 pg/ml); 35% had a prior HF hospitalization, and both KCCQ-CSS (mean 53.6, indicating poor QOL) and 6MWD (303 meters) were severely reduced. Of the randomized patients, 81% had evidence of LV hypertrophy, 91% had evidence of left atrial enlargement, and 73% had evidence of both. As shown in Figure 1, dyspnea and fatigue were the most common symptoms, followed by orthopnea. Edema was the most common sign of HF on physical exam at the time of enrollment. Patients enrolled in PARALLAX had slightly more dyspnea at rest, orthopnea, and edema, and more often had fatigue compared to PARAGON-HF. Prevalence of jugular venous distension was slightly lower in PARALLAX compared to PARAGON-HF.
Table 1.
Baseline Characteristics of Patients Enrolled in the PARALLAX trial by Enrollment Strata
| Characteristic | All patients (N=2566) | ACE-inhibitor (N=1066) | ARB (N=1174) | No RASi (N=326) | P-value across 3 strata | P-value RASi vs. no RASi |
|---|---|---|---|---|---|---|
|
| ||||||
| Age, y | 72.6±8.5 | 72.0±8.3 | 73.0±8.5 | 73.0±8.8 | 0.013 | 0.36 |
| Female, n(%) | 1301 (50.7) | 463 (43.4) | 661 (56.3) | 177 (54.3) | <0.001 | 0.18 |
| Race/ethnicity, n(%) | <0.001 | <0.001 | ||||
| • Native American | 72 (2.8) | 15 (1.4) | 53 (4.5) | 4 (1.2) | ||
| • Asian | 115 (4.5) | 19 (1.8) | 65 (5.5) | 31 (9.5) | ||
| • Black | 27 (1.0) | 9 (0.8) | 13 (1.1) | 5 (1.5) | ||
| • White | 2229 (86.9) | 996 (93.4) | 961 (81.9) | 272 (83.4) | ||
| • Other | 123 (4.8) | 27 (2.6) | 81 (6.9) | 14 (4.3) | ||
| Region, n(%) | <0.001 | <0.001 | ||||
| • North America | 132 (5.1) | 40 (3.8) | 51 (4.3) | 41 (12.6) | ||
| • Latin/Central America | 356 (13.9) | 84 (7.9) | 236 (20.1) | 36 (11.0) | ||
| • Europe | 1939 (75.6) | 916 (85.9) | 811 (69.1) | 212 (65.0) | ||
| • Asia/Pacific/other | 139 (5.4) | 26 (2.4) | 76 (6.5) | 37 (11.4) | ||
| HF characteristics | ||||||
| • HF etiology, n(%)* | ||||||
| ∘ Ischemic | 892 (34.8) | 417 (39.1) | 372 (31.7) | 103 (31.6) | 0.001 | 0.22 |
| ∘ Non-ischemic | ||||||
| • Hypertensive | 1488 (58.0) | 600 (56.3) | 740 (63.0) | 148 (45.4) | <0.001 | <0.001 |
| • Diabetic | 218 (8.5) | 88 (8.3) | 197 (9.1) | 23 (23.1) | 0.47 | 0.37 |
| • Other | 246 (9.6) | 84 (7.9) | 1 (0.1) | 87 (26.7) | <0.001 | <0.001 |
| • Baseline LVEF, %-units | 56.5±8.2 | 55.7±8.2 | 57.0±8.2 | 56.8±8.0 | <0.001 | 0.35 |
| ∘ LVEF < 50%, n(%) | 501 (19.5) | 237 (22.2) | 215 (18.5) | 49 (15.3) | ||
| • NYHA class at randomization, n(%) | 0.94 | 0.80 | ||||
| ∘ Class I | 5 (0.2) | 2 (0.2) | 2 (0.2) | 1 (0.3) | ||
| ∘ Class II | 1734 (67.6) | 729 (68.4) | 784 (66.8) | 221 (67.8) | ||
| ∘ Class III | 817 (31.8) | 331 (31.0) | 384 (32.7) | 102 (31.3) | ||
| ∘ Class IV | 9 (0.4) | 3 (0.3) | 4 (0.4) | 2 (0.6) | ||
| • Prior HF hospitalization, n(%) | 905 (35) | 420 (39.4) | 359 (30.6) | 126 (38.6) | <0.001 | 0.19 |
| • NTproBNP, pg/ml** | 769 (399,1399) | 798 (426,1430) | 705 (372,1329) | 879 (438,1614) | <0.001 | 0.006 |
| • KCCQ clinical summary score | 53.0±16.8 | 53.6±16.3 | 52.6±16.8 | 52.4±18.2 | 0.27 | 0.50 |
| • KCCQ physical limitation score | 49.5±19.2) | 50.1±18.9 | 49.3±18.9 | 48.5±20.7 | 0.37 | 0.28 |
| • KCCQ symptom burden score | 57.8±19.7) | 58.1±19.3 | 57.5±19.6 | 57.4±21.4 | 0.72 | 0.72 |
| • KCCQ symptom frequency score | 55.1±20.3) | 56.1±19.4 | 54.2±20.7 | 55.1±22.0 | 0.09 | 0.99 |
| • KCCQ total symptom score | 56.4±18.6) | 57.1±17.9 | 55.9±18.6 | 56.2±20.4 | 0.27 | 0.84 |
| • SF-36 general health score | 44.2±16.0 | 44.1±16.1 | 43.9±15.5 | 46.4±17.8 | 0.036 | 0.01 |
| • SF-36 physical functioning score | 35.2±18.8 | 36.4±18.5 | 34.2±18.6 | 34.7±20.6 | 0.023 | 0.65 |
| • Baseline 6MWD, meters | 303.3±105.4 | 310.8±102.0 | 296.3±106.1 | 303.8±112.0 | 0.005 | 0.92 |
| • 6MWD categories, n(%) | 0.37 | 0.26 | ||||
| ∘ 6MWD < 100 meters | 66 (2.6) | 23 (2.2) | 35 (3.0) | 8 (2.4) | ||
| ∘ 6MWD 100–450 meters | 2313 (90.1) | 960 (90.1) | 1051 (89.5) | 302 (92.6) | ||
| ∘ 6MWD > 450 meters | 181 (7.0) | 80 (7.5) | 85 (7.2) | 16 (4.9) | ||
| • HF signs and symptoms, n(%) | ||||||
| ∘ Dyspnea at rest | 173 (6.7) | 63 (5.9) | 81 (6.9) | 29 (8.9) | 0.17 | 0.12 |
| ∘ Dyspnea with effort | 2515 (98.1) | 1047 (98.3) | 1150 (98.0) | 318 (97.5) | 0.65 | 0.62 |
| ∘ Edema | 1296 (50.5) | 545 (51.2) | 597 (50.9) | 154 (47.2) | 0.44 | 0.23 |
| ∘ Jugular venous distension | 1899 (74.0) | 815 (76.5) | 842 (71.7) | 242 (74.2) | 0.035 | 0.98 |
| ∘ Fatigue | 347 (13.5) | 125 (11.7) | 179 (15.2) | 43 (13.2) | 0.052 | 0.92 |
| ∘ Orthopnea | 715 (27.9) | 288 (27.0) | 336 (28.6) | 91 (27.9) | 0.701 | 0.99 |
| ∘ Paroxysmal nocturnal dyspnea | 261 (10.2) | 98 (9.2) | 132 (11.2) | 31 (9.5) | 0.26 | 0.74 |
| ∘ Rales | 329 (12.8) | 147 (13.8) | 133 (11.3) | 49 (15.0) | 0.10 | 0.24 |
| ∘ Third heart sound | 92 (3.6) | 49 (4.6) | 38 (3.2) | 5 (1.5) | 0.023 | 0.048 |
| Comorbidities, n(%) | ||||||
| • Hypertension | 2492 (97.1) | 1063 (99.7) | 1171 (99.7) | 258 (79.1) | <0.001 | <0.001 |
| • Diabetes mellitus | 1030 (40.1) | 428 (40.2) | 556 (47.4) | 102 (31.3) | 0.001 | 0.001 |
| • Dyslipidemia | 1719 (67.0) | 765 (71.8) | 785 (66.9) | 169 (51.8) | <0.001 | <0.001 |
| • Atrial fibrillation on screening ECG | 966 (37.7) | 442 (41.5) | 394 (33.6) | 130 (39.9) | <0.001 | 0.41 |
| • Atrial fibrillation at any time in the past | 1391 (54.2) | 619 (58.1) | 578 (49.2) | 194 (59.5) | <0.001 | 0.046 |
| • Coronary artery disease | 1368 (53.3) | 611 (57.3) | 617 (52.5) | 141 (43.2) | <0.001 | <0.001 |
| • Myocardial infarction | 601 (23.4) | 295 (27.7) | 246 (21.0) | 60 (18.4) | <0.001 | 0.026 |
| • Coronary artery bypass grafting | 348 (13.6) | 152 (14.3) | 140 (11.9) | 56 (17.2) | 0.034 | 0.051 |
| • Percutaneous coronary intervention | 620 (24.2) | 283 (26.6) | 260 (22.2) | 77 (23.6) | 0.051 | 0.86 |
| • Asthma | 160 (6.2) | 61 (5.7) | 80 (6.8) | 19 (5.8) | 0.54 | 0.84 |
| • Chronic obstructive pulmonary disease | 318 (12.4) | 147 (13.8) | 128 (10.9) | 43 (13.2) | 0.11 | 0.71 |
| • Obstructive sleep apnea | 198 (7.7) | 76 (7.1) | 93 (7.9) | 29 (8.9) | 0.54 | 0.46 |
| Physical characteristics and lab data | ||||||
| • Body-mass index, kg/m2 | 30.6±4.9 | 30.8±4.8 | 30.5±4.8 | 29.9±5.2 | 0.007 | 0.006 |
| • Height, cm | 166.0±10.1 | 167.7±9.9 | 164.8±10.0 | 165.0±10.5 | <0.001 | 0.06 |
| • Weight, kg | 84.6±17.2 | 87.1±17.5 | 83.2±16.5 | 81.8±17.7 | <0.001 | 0.002 |
| • Heart rate, beats/min | 70.7±11.9 | 71.1±12.1 | 69.8±11.4 | 72.1±12.4 | 0.001 | 0.015 |
| • Systolic BP, mmHg | 133.4±14.3 | 133.6±13.7 | 134.0±14.4 | 130.6±15.2 | 0.001 | <0.001 |
| • Diastolic BP, mmHg | 77.2±10.2 | 78.2±9.9 | 76.7±10.4 | 75.7±10.4 | <0.001 | 0.006 |
| • Hemoglobin, g/dL | 13.5±1.6 | 13.7±1.6 | 13.4±1.6 | 13.3±1.6 | <0.001 | 0.012 |
| • Serum creatinine, mmol/dL | 96.8±28.6 | 97.4±28.2 | 95.9±30.0 | 98.2±28.7 | 0.27 | 0.55 |
| • eGFR, ml/min/1.73 m2 | 62.6±19.9 | 63.3±20.1 | 62.4±19.9 | 60.7±19.3 | 0.20 | 0.11 |
| Medications at randomization, n(%) | ||||||
| • ACE-inhibitor | 1067 (41.6) | 1055 (99.1) | 6 (0.5) | 6 (1.8) | <0.001 | <0.001 |
| • Angiotensin receptor blocker | 1178 (45.9) | 5 (0.5) | 1167 (99.4) | 6 (1.8) | <0.001 | <0.001 |
| • Diuretic | 2559 (99.8) | 1063 (99.8) | 1172 (99.8) | 324 (99.7) | 0.30 | 0.22 |
| • MRA | 811 (31.6) | 343 (32.2) | 343 (29.2) | 125 (38.5) | 0.006 | 0.005 |
| • Beta-blocker | 2137 (83.4) | 932 (87.5) | 944 (80.4) | 261 (80.3) | <0.001 | 0.10 |
| • Calcium channel blocker | 923 (36.0) | 376 (35.3) | 358 (39.0) | 89 (27.4) | 0.008 | 0.048 |
| • Nitrate | 294 (11.5) | 154 (14.5) | 140 (11.9) | 46 (14.2) | 0.19 | 0.62 |
| • SGLT2-inhibitor | 60 (2.3) | 19 (1.8) | 34 (2.9) | 7 (2.2) | 0.21 | 0.81 |
| • Statin | 1732 (67.6) | 779 (73.2) | 825 (70.3) | 203 (62.5) | 0.001 | 0.001 |
| • Anticoagulant | 1356 (52.9) | 647 (60.8) | 600 (51.1) | 197 (60.6) | <0.001 | 0.11 |
| • Aspirin | 881 (34.4) | 362 (34.0) | 442 (37.7) | 105 (32.3) | 0.08 | 0.19 |
Patients could have > 1 etiology of HF as determined by the site investigator
Values represent median (25th-75th percentile)
BP = blood pressure; HF = heart failure; LVEF = left ventricular ejection fraction; NYHA = New York Heart Association class; NTproBNP = N-terminal pro-B-type natriuretic peptide; KCCQ = Kansas City Cardiomyopathy Questionnaire; 6MWD = 6-minute walk distance; ECG = electrocardiography; eGFR = estimated glomerular filtration rate; ACE = angiotensin converting enzyme; MRA = mineralocorticoid receptor antagonist; SGLT2 = sodium-glucose co-transporter-2.
Figure 1. Signs and Symptoms of Heart Failure in Patients Enrolled in the PARALLAX Trial.
Between group comparisons were made with Chi-squared tests. PND = paroxysmal nocturnal dyspnea; JVP = jugular venous pressure; S3 = third heart sound.
Baseline demographics, clinical characteristics, comorbidities, and medications
Table 1 displays the baseline characteristics for all patients enrolled in the PARALLAX trial and stratified by randomization strata. Overall, there was a slight female predominance (51%) and mean age was 73 years. The majority of the participants (87%) were white, and hypertensive heart disease was the most common etiology of HF. Comorbidities were common: almost all patients had hypertension (97% prevalence), but blood pressure was relatively well controlled in most (mean SBP 133 mmHg); over half were obese; and more than half (54%) had a history of AF at some time in the past. Nearly all patients were on diuretic therapy and over 83% were taking beta-blockers, with the majority on multiple anti-hypertensive medications. Approximately one-third of patients were taking mineralocorticoid receptor antagonists (MRAs).
Of the 2566 total randomized patients in PARALLAX, 1066 (41.5%) were taking an ACE-inhibitor, 1174 (45.8%) were taking an ARB, and 326 (12.7%) were on neither (no RAS-inhibitor therapy) at the screening visit. In general, the 3 randomization strata were similar, though there were some differences. Patients in the ACE-inhibitor strata were slightly younger, more often male, more often white, more often from Europe, and were more likely to have an ischemic etiology of their HF. These patients also had a slightly lower LVEF, slightly higher eGFR, and were more likely to have dyslipidemia, AF on the screening ECG, prior HF hospitalization, CAD, and MI, and were more likely taking beta-blockers. Compared with patients on RAS inhibitor therapy, those who were not on RAS inhibitor therapy were more often Asian and from the Asia/Pacific region, less likely to have hypertension or a hypertensive etiology of HF, had a higher NTproBNP, had lower BMI and blood pressure, and had lower frequencies of most comorbidities except for atrial fibrillation.
Supplemental Table S2 compares enrolled patients with preserved LVEF (> 50%) vs. mildly reduced LVEF (41–50%). Patients with mildly reduced LVEF (n=767) were younger; less commonly female; more often had ischemic etiology, coronary artery disease, myocardial infarction, coronary revascularization, prior HF hospitalization, and more signs and symptoms of HF; had higher heart rate, diastolic blood pressure, NTproBNP, hemoglobin, and estimated GFR; and had lower hip circumference and systolic blood pressure and worse KCCQ symptoms scores compared to patients with LVEF > 50% (n=1799). The major differences between the 2 groups were sex (male), etiology of HF (ischemic) and related coronary artery disease history, prior HF hospitalization, and higher NTproBNP in the subgroup with LVEF 40–50%.
Association of baseline characteristics with NTproBNP, quality of life, and exercise capacity
The mean KCCQ clinical summary score was 53, and the mean 6WMD was 303 meters. These values were similar across RASi therapy-based strata (Table 1). Figure 2 displays a correlation heatmap of NTproBNP, KCCQ scores, SF-36 scores, NYHA class, 6MWD, and signs/symptoms of HF. Of the QOL scores, SF-36 physical functioning score was most closely correlated with 6MWD (R=0.41; higher correlation than the KCCQ physical limitation score [R=0.33] and KCCQ-CSS [R=0.31]). NYHA class was less correlated to 6MWD (R=−0.22), and of the HF signs/symptoms, orthopnea correlated best with 6MWD (R=−0.17). NTproBNP did not correlate well with any of the QOL scores or HF signs and symptoms and was only loosely correlated with NYHA class (R=0.10) and 6MWD (R=−0.09).
Figure 2. Correlation Heatmap of NTproBNP, 6-Minute Walk Test Distance, Quality of Life Scores, and Signs and Symptoms of Heart Failure.
Values in cells represent Pearson correlation coefficients. Correlations of scores within the same questionnaire/survey (KCCQ or SF-36) are blacked out because these reflect summary scores or components of the summary scores and therefore by definition are correlated. 6MWD = 6-minute walk test distance; KCCQ = Kansas City Cardiomyopathy Questionnaire; SF-36 = Short Form Health Survey; NTproBNP = N-terminal pro-B-type natriuretic peptide; S3 = third heart sounds; NYHA = New York Heart Association. Variables were ordered based on hierarchical clustering using hclust in R.
Supplementary Tables S3–S5 compared baseline characteristics across tertiles of NTproBNP, KCCQ clinical summary score, and 6MWD. Comorbidities differed across NTproBNP tertiles to a greater extent than across KCCQ and 6MWD tertiles; whereas HF signs and symptoms varied to a greater extent across KCCQ and 6MWD tertiles compared to NTproBNP tertiles.
Supplementary Tables S6–S8 display the multivariable analysis of baseline characteristics associated with NTproBNP, KCCQ-CSS, and 6MWD, respectively. Several baseline characteristics were associated with higher values of log-transformed NTproBNP on multivariable analysis (Table S6) after adjusting for multiple comparisons, including older age, male sex, history of AF, worse renal function (lower eGFR), lower hemoglobin, higher NYHA class, prior HF hospitalization, and lower LVEF. Enrollment in the Asia/Pacific region (compared to North America), ARB use, higher BMI, and history of CAD were associated with lower levels of NTproBNP.
Female sex, Latin/Central America region, higher BMI, lower hemoglobin, history of CAD, NYHA class III or IV, lower LVEF, and higher NTproBNP were all independently associated with worse (lower) KCCQ-CSS after adjustment for multiple comparisons (Table S7). Despite higher NTproBNP levels in AF (median 1079 [25th-75th percentile 660–1721] pg/ml) compared to no AF (461 [295–856]) pg/ml (P<0.0001), history of AF was associated with better KCCQ-CSS on multivariable analysis.
Older age, female sex, non-European regions, higher BMI, lower hemoglobin, diabetes, COPD, higher NYHA class, lower KCCQ-CSS, higher NTproBNP, prior HF hospitalization, and lower LVEF were all independently associated with worse (shorter) 6MWD after adjustment for multiple comparisons (Table S8). AF was associated with greater 6MWD in the fully adjusted model. In all regression models (including the fully adjusted model), the SF-36 physical functioning score was more closely associated with 6MWD than the KCCQ physical limitation and KCCQ-CSS (and the KCCQ physical limitation score outperformed the KCCQ-CSS in the association with 6MWD) (Supplemental Table S9). In all regression analyses of QOL measures with 6MWD, none of the covariates (except for NYHA class, which is also a measure of functional status) changed the beta-coefficient for the association between QOL measures and 6MWD by > 10%. Shorter height and higher weight (included as separate predictor variables), which were both independently associated with lower 6MWD in all multivariable models, were more strongly associated with 6MWD than BMI (Supplemental Table S9).
Comparison to prior HFpEF clinical trials
Overall, characteristics of PARALLAX participants were similar to those reported in large-scale HFpEF randomized clinical trials1, 9–20 (Supplementary Table S10). PARALLAX exceeded all other trials in frequency of hypertension history (97%), had lower frequency of history of HF hospitalization compared to PARAGON-HF, TOPCAT-Americas, and CHARM-Preserved, and greater MRA use compared to any other large-scale HFpEF RCT. Compared to PARAGON-HF, baseline characteristics were very similar except for some notable differences, including higher prevalence of CAD, lower NTproBNP, and greater frequency of beta-blocker use in PARALLAX. History of AF was common in both trials and much higher than in the other trials listed in Supplementary Table S10.
Supplementary Table S11 compares PARALLAX to recent multicenter, randomized HFpEF clinical trials1, 10, 12–17, 21–25 that included either KCCQ or 6MWD. PARALLAX had the lowest KCCQ scores, even slightly lower than SOCRATES-Preserved, which recruited patients with worsening HFpEF shortly after HF hospitalization. In terms of 6MWD, PARALLAX was among the trials with the lowest values, indicating poor exercise capacity.
DISCUSSION
PARALLAX, which compared the efficacy of sacubitril/valsartan to individualized RAS-inhibitor therapy, is the largest randomized clinical trial to date that examined exercise capacity in patients with HFpEF. In addition, PARALLAX specifically focused on patients with significantly reduced QOL (KCCQ-CSS < 75). PARALLAX participants display several features that are typical of the broader population with HFpEF. Namely, the mean age of patients enrolled in PARALLAX was 73 years at baseline, with a female predominance and a very high prevalence of multiple comorbidities, especially a history of systemic hypertension. In addition, by design, patients enrolled in PARALLAX had objective evidence of HFpEF. Patients were symptomatic (NYHA class II and III) with reduced exercise capacity, had LV hypertrophy and/or left atrial enlargement, elevated NTproBNP, preserved LVEF, and often had a prior history of HF hospitalization. In addition to describing the overall baseline characteristics for the PARALLAX trial, we also investigated differences in clinical characteristics among the 3 randomization strata (ACE-I, ARB, no RASi groups) and the relationship between NTproBNP, 6MWD, KCCQ, SF-36, and HF signs/symptoms as discussed below and displayed in the Graphical Abstract.
Baseline quality of life and exercise capacity in PARALLAX
QOL, as measured by the KCCQ, has been validated in HFpEF5, 26 and can improve in response to medical therapy, as shown in the TOPCAT trial.27 In PARALLAX, QOL was severely impaired with KCCQ-CSS values that were lower than all other recent HFpEF trials in which it was measured, and even lower than SOCRATES-Preserved, which specifically examined patients with worsening HFpEF who had a very recent HF hospitalization. The low QOL in PARALLAX is not unexpected given the fact that KCCQ-CSS < 75 was one of the inclusion criteria. Nevertheless, the KCCQ-CSS in PARALLAX was lower than generally reported in chronic HFrEF5, 27–30 and was worse than patients with stage 5 chronic kidney disease (eGFR < 30 ml/min/m2) enrolled in the Chronic Renal Insufficiency Cohort (CRIC) study.31 6MWD was also severely reduced in PARALLAX, and worse than values reported in recent randomized, multicenter HFpEF clinical trials, as described in detail below.
NTproBNP, KCCQ clinical summary score, and 6MWD in PARALLAX
In PARALLAX, there was a modest correlation between KCCQ-CSS and 6MWD. The KCCQ physical limitation score correlated slightly better with 6MWD, and the SF-36 physical functioning score was the QOL measure that correlated best with 6MWD. In addition, the correlation between NTproBNP and QOL measures and 6MWD was poor. These results suggest that these 3 variable types (NTproBNP, QOL measures, and 6MWD) provide orthogonal views of the patient journey in HFpEF. NTproBNP is reflective of congestion but can be elevated in the setting of AF and may not be specific for congestion in these patients. Although the KCCQ and SF-36 assess the impact of HF on QOL, these measures can be influenced by non-HF and non-cardiac factors. Finally, although one of the exclusion criteria in PARALLAX is the presence of clinically relevant non-cardiac cause of exercise intolerance, non-cardiac comorbidities play a role in limiting 6MWD even if the HF syndrome is the main reason for reduced exercise capacity. Obesity, which was present in over half of PARALLAX participants and is associated with lower (better) NTproBNP levels while also associated with lower (worse) KCCQ-CSS and 6MWD values, is an example of how the association of certain characteristics with these parameters can differ in the setting of HFpEF.
On multivariable analysis, there were several baseline characteristics which were associated with NTproBNP, KCCQ-CSS, and 6MWD, with some commonalities between the 3 parameters, as well as some characteristics that diverged between NTproBNP, QOL, and exercise capacity. Prior HF hospitalization and lower LVEF were common factors associated with worse values of all 3 parameters. Divergent factors were female sex, BMI, CAD, and AF. Female sex, higher BMI, and CAD were associated with lower NTproBNP values but worse KCCQ-CSS and 6MWD, whereas history of AF was associated with higher (worse) NTproBNP values but better KCCQ-CSS and 6MWD values in fully adjusted models. The latter finding was unexpected. Several studies on AF in HFpEF have noted that the presence of AF is associated with worse QOL, worse exercise tolerance, and worse outcomes.32, 33 The fact that the opposite was seen in PARALLAX suggests that despite the higher NTproBNP threshold for patients with AF at the time of screening, patients in PARALLAX who had paroxysmal AF could have gotten into the trial with the lower NTproBNP threshold (>220 pg/ml). Thus, some of the patients with HFpEF and history of AF enrolled in PARALLAX may have been healthier than expected, which is supported by the finding that these patients had better QOL and exercise capacity. In future trials, patients with a history of AF may require additional criteria besides NTproBNP to confirm that they truly have significant HF as a cause of their symptoms, particularly for medications that promote natriuresis such as ARNIs and diuretics, which aim to decongest the patient.
In the multivariable regression model for 6MWD, the SF-36 physical functioning score consistently outperformed KCCQ-CSS and KCCQ physical limitation score as a predictor of 6MWD in all multivariable models. In addition, inclusion of height and weight separately outperformed BMI as predictors of 6MWD in all multivariable models likely because height is a significant determinant of 6MWD,34 which may be masked when included in BMI.
Comparison of PARALLAX to other HF clinical trials
Compared to prior large-scale multi-center HFpEF clinical trials, characteristics of PARALLAX participants were generally similar with some notable differences. The very high prevalence of hypertension (97%) in PARALLAX, which was higher than prior trials, likely reflects the fact that for 2 of the RAS-inhibitor strata (ACE-I and ARB), history of hypertension (as the main reason for RAS-inhibitor therapy) was required. MRA use appears to be increasing over time from 15% in I-PRESERVE to 24% in PARAGON-HF to 32% in PARALLAX, likely reflecting the results of the TOPCAT trial and the guideline-based recommendation for MRAs in HFpEF. The baseline characteristics of PARALLAX were quite similar to PARAGON-HF, likely reflecting the similar entry criteria. The lower NTproBNP and KCCQ-CSS values were consistent with the lower NTproBNP threshold and requirement for KCCQ-CSS < 75 in PARALLAX. History of AF was common (>50%) in both PARALLAX and PARAGON, and much higher than the prior large-scale HFpEF RCTs, which likely reflects the requirement for elevated NTproBNP for entry into these trials. As stated above, patients with AF have higher NTproBNP levels in the general population, and thus, patients with paroxysmal AF who were not in AF at the time of screening may have been able to more easily achieve the lower NTproBNP threshold (> 220 pg/ml for those in sinus rhythm at screening), allowing for a greater percentage of patients with a history of AF in the trial.
Baseline characteristics associated with QOL (KCCQ overall summary score) were examined in the PARAGON-HF trial using forward multivariable stepwise regression modeling. In PARAGON-HF, female sex, higher BMI, COPD, higher NTproBNP, and several symptoms and signs of HF and cardiovascular disease (e.g., lower extremity edema, angina, S3, dyspnea on exertion, paroxysmal nocturnal dyspnea) were all associated with worse QOL.28 Thus, both PARALLAX and PARAGON consistently found that female sex, higher BMI, and higher NTproBNP are each independently associated with worse QOL in HFpEF.
Several recent multicenter HFpEF clinical trials1, 10, 12, 13, 15–17, 21–25 have included KCCQ and 6MWD, though none of the prior trials testing exercise capacity has been nearly as large as PARALLAX. KCCQ-CSS scores, by design, were low in PARALLAX, and thus reflected a group of HFpEF patients with low QOL despite the preponderance of NYHA class II patients and only 30% with a prior HF hospitalization. This differs from SOCRATES-Preserved, which included patients mainly with NYHA class III symptoms who were recently hospitalized and yet had a slightly higher KCCQ-CSS score at baseline. The reasons for this discrepancy are unclear but may reflect causes other than congestion for low QOL in the PARALLAX trial. The mean value of 6MWD in PARALLAX was among the lowest of recent multicenter HFpEF trials, despite somewhat lower NTproBNP values compared to some, a finding that may also support the notion that cardiac and non-cardiac causes other than congestion could have been underlying the low exercise capacity and QOL in PARALLAX patients.
Predictors of QOL and 6MWD were examined in the HF-ACTION trial in HFrEF patients.35, 36 The correlation coefficients for KCCQ-CSS (R=0.32) and KCCQ physical limitation score (R=0.35) with 6MWD in HF-ACTION were similar to those found in HFpEF patients in PARALLAX. In both studies, age, height, weight, NYHA class, NTproBNP, and HF hospitalizations were predictors of 6MWD, which demonstrates consistencies of these associations across the spectrum of LVEF in patients with HF.
Strengths and limitations
Besides its novel study design, which compares sacubitril/valsartan to individualized baseline RAS-inhibitor use-based medical therapy, the strengths of PARALLAX also include the large number of patients who underwent 6MWT for determination of exercise capacity (the largest trial to date to do so) and the clear evidence for a diagnosis of HF in the study patients. Because almost all patients underwent NTproBNP, KCCQ, and 6MWT, we were able to determine how these parameters correlated with each other, and we were able to determine baseline characteristics associated with each of these 3 domains on multivariable linear regression analysis. Despite these strengths, certain limitations should be taken into consideration when interpreting the baseline characteristics in PARALLAX. The specific inclusion/exclusion criteria for PARALLAX were quite broad but designed to select a specific type of HFpEF patient; thus, the associations examined in PARALLAX may not be entirely representative in the general population. This is certainly the case with history of AF, which was associated with better QOL and exercise capacity in fully adjusted models; however, for other parameters, the associations are in line with previously known pathophysiology of HFpEF. Furthermore, although we included asthma, COPD, and OSA in our multivariable models, we did not have data on severity of lung disease, which could have provided greater insight into the variables associated with 6MWD. We were also not able to directly compare several aspects of PARALLAX to other HFpEF trials/studies, as there were differences among the HFpEF trials/studies for variables that were collected and reported.
CONCLUSIONS
PARALLAX is a contemporary HFpEF trial that is testing the effects of sacubitril/valsartan vs. individualized RAS-inhibition therapy on NTproBNP, exercise capacity, and QOL. It is by far the largest HFpEF study to date to examine 6MWD. Patients enrolled in PARALLAX were similar to other contemporary HFpEF clinical trials except QOL was lower, likely because of the requirement of reduced KCCQ for inclusion into the trial. The baseline KCCQ-CSS and 6MWD were modestly correlated, and several factors were associated with worse values of both. The SF-36 physical functioning score was the QOL measure that was most closely associated with 6MWD. These results provide insight into the association between QOL and exercise capacity in HFpEF.
Supplementary Material
FUNDING
The PARALLAX trial is funded and sponsored by Novartis. SJS is supported by grants from the National Institutes of Health (R01 HL107577, R01 HL127028, R01 HL140731, and R01 HL149423) and the American Heart Association (#16SFRN28780016).
DISCLOSURES
SJS has received research grants from Actelion, AstraZeneca, Corvia, Novartis, and Pfizer; and has served as a consultant, scientific advisory board member, and/or executive committee/steering committee member for Abbott, Actelion, AstraZeneca, Amgen, Axon Therapeutics, Bayer, Boehringer-Ingelheim, Bristol-Myers Squibb, Cardiora, CVRx, Cytokinetics, Eisai, GSK, Ionis, Ironwood, Merck, MyoKardia, Novartis, Pfizer, Sanofi, Shifamed, Tenax, and United Therapeutics. MRC received grants from Medtronic, Boston Scientific, Abbott, Bayer and ResMed during the conduct of the study; and has served as a consultant/advisor/steering committee member for Novartis, Servier, Bayer, Boston Scientific, Abbott, ResMed, AstraZeneca, NovoNordisk, Neurotronik, and Fire1Foundry. RW received grants from BMBF, Boehringer Ingelheim, DFG and European Union; personal fees and/or investigator fees from Bayer, Berlin Chemie, Boehringer Ingelheim, Medtronic, Novartis, Servier, Bristol-Myers Squibb, Pfizer, Sanofi and CVRx; Boston Scientific, Gilead, Johnson & Johnson. BP is the Principal Investigator of PARALLAX and received personal and institutional honoraria from Novartis for steering committee, advisory board, and speaker activities. BP also received steering committee and/or speaker fees from Bayer Healthcare, Merck, Daiichi-Sankyo, Servier, BMS, and AstraZeneca. All other authors are employees of Novartis.
Footnotes
Clinical Trials Registration Information:ClinicalTrials.govidentifier:NCT03066804 (http://www.clinicaltrials.gov/ct2/show/NCT03066804)
Sponsor: Novartis Pharmaceuticals, Inc.
Contributor Information
Sanjiv J. Shah, Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Martin R. Cowie, Imperial College, London, UK.
Rolf Wachter, Clinic and Policlinic for Cardiology, University Hospital Leipzig, Leipzig, Germany, and Clinic for Cardiology and Pneumology, University Medicine Göttingen and DZHK (German Center for Cardiovascular Research), partner site Göttingen, Germany.
Peter Szecsödy, Novartis, Basel, Switzerland.
Victor Shi, Novartis, East Hanover, NJ, USA.
Ghionul Ibram, Novartis, East Hanover, NJ, USA.
Mo Hu, Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Ziqiang Zhao, Novartis, Shanghai, China.
Jianjian Gong, Novartis, East Hanover, NJ, USA.
Burkert Pieske, Department of Internal Medicine and Cardiology, Campus Virchow Klinikum, Charité University Medicine; Department of Internal Medicine and Cardiology, German Heart Center; DZHK (German Center for Cardiovascular Research), partner site Berlin; and Berlin Institute of Health, Berlin, Germany.
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