# Natriuretic Peptides, Body Mass Index, and Clinical Outcomes in Heart Failure With Mildly Reduced or Preserved Ejection Fraction

John W Ostrominski, Brendon L Neuen, Brian L Claggett, Inder S Anand, Akshay S Desai, Pardeep S Jhund, Carolyn S.P. Lam, Marc A Pfeffer, Bertram Pitt, Faiez Zannad, et al.

► To cite this version:

John W Ostrominski, Brendon L Neuen, Brian L Claggett, Inder S Anand, Akshay S Desai, et al. Natriuretic Peptides, Body Mass Index, and Clinical Outcomes in Heart Failure With Mildly Reduced or Preserved Ejection Fraction. Journal of the American College of Cardiology, 2025, 86 (20), pp.1823-1839. 10.1016/j.jacc.2025.08.028. hal-05444759

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# Natriuretic Peptides, Body Mass Index, and Clinical Outcomes in Heart Failure with Mildly Reduced or Preserved Ejection Fraction

John W. Ostrominski, MD<sup>1,2</sup>; Brendon L. Neuen, MBBS, MSc, PhD<sup>3,4</sup>; Brian L. Claggett, PhD<sup>1</sup>;
Inder S. Anand, MD<sup>5</sup>; Akshay S. Desai, MD<sup>1</sup>; Pardeep S. Jhund, MBChB MSc PhD<sup>6</sup>; Carolyn
S.P. Lam, MBBS PhD<sup>7</sup>; Marc A. Pfeffer, MD PhD<sup>1</sup>; Bertram Pitt, MD<sup>8</sup>; Faiez Zannad, MD
PhD<sup>9</sup>; Michael R. Zile, MD<sup>10</sup>; Milton Packer, MD<sup>11</sup>; Kieran F Docherty, MB ChB PhD<sup>2</sup>;
John J.V. McMurray, MD<sup>6</sup>; Scott D. Solomon, MD<sup>1</sup>; Muthiah Vaduganathan, MD MPH<sup>1</sup>

<sup>1</sup>: Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA

<sup>2</sup>: Division of Endocrinology, Diabetes and Hypertension, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA

<sup>3</sup>: The George Institute for Global Health, University of New South Wales, Sydney, Australia

<sup>4</sup>: Department of Renal Medicine, Royal North Shore Hospital, Sydney, Australia

<sup>5</sup>: Veterans Affairs Medical Center and University of Minnesota, Minneapolis, MN, USA

<sup>6</sup>: British Heart Foundation Cardiovascular Research Centre, University of Glasgow, Glasgow, UK

<sup>7</sup>: National Heart Centre Singapore and Duke-National University of Singapore, Singapore

<sup>8</sup>: Department of Medicine, University of Michigan School of Medicine, Ann Arbor, MI, USA

<sup>9</sup>: Université de Lorraine, Inserm Clinical Investigation Centre, CHU, Nancy, France

<sup>10</sup>: Ralph H. Johnson Veterans Affairs Medical Center and Medical University of South Carolina, Charleston, SC, USA

<sup>11</sup>: Baylor Scott & White Health, Dallas, TX, USA

## Address for Correspondence:

Muthiah Vaduganathan, MD MPH
Cardiovascular Division
Brigham and Women's Hospital
Harvard Medical School
75 Francis St
Boston MA 02115

Email: mvaduganathan@bwh.harvard.edu

X/Twitter: @mvaduganathan

## Funding Support and Author Disclosures

**Dr. Ostrominski** reports grant support from the National Institutes of Health (5T32HL007604-39 and L30HL175757). **Dr. Neuen** is supported by an Australian National Health and Medical Research Council Emerging Leader Investigator Grant (grant number 2026621) and a Ramaciotti Foundation Health Investment Grant (grant number 2023HIG69), and has received fees for travel support, advisory boards, and scientific presentations from AstraZeneca, Bayer, Boehringer and Ingelheim, Cambridge Healthcare Research, Cornerstone Medical Education, the Limbic, Janssen, Medscape, Novo Nordisk, and Travere Therapeutics; and has served on clinical trial committees for studies sponsored by AstraZeneca, Bayer, and CSL Behring. **Dr. Claggett** reports personal fees from Alnylam, personal fees from Cardior, personal fees from Cardurion, personal fees from Corvia, personal fees from Cytokinetics, personal fees from CVRx, personal fees from
Intellia, personal fees from Rocket, outside the submitted work. **Dr. Anand** reports receiving consultancy fees from Amgen, ARCA, AstraZeneca, Boehringer Ingelheim, Boston Scientific, LivaNova, Novartis, Rockwell Medical, and Zensun. **Dr. Desai** has received honoraria for consulting or speaking from Abbott, AstraZeneca, Alnylam, Avidity Biopharma, Axon Therapeutics, Bayer, Biofourmis, Boston Scientific, GlaxoSmithKline, Medpace, Medtronic, Merck, New Amsterdam Pharma, Novartis, Parexel, Regeneron, River2Renal, Roche, scPharmaceuticals, Verily, Veristat, and Zydus and has received institutional research grant support from Abbott, Alnylam, AstraZeneca, Bayer, Novartis, and Pfizer. **Dr. Jhund** reports personal fees from Bayer, during the conduct of the study; other from Novartis, from AstraZeneca, grants from AstraZeneca, other from Novo Nordisk, grants from Boehringer Ingelheim, grants from Analog Devices, grants from Roche Diagnostics, personal fees from ProAdwise Communications, personal fees from Intas Pharma, personal fees from Sun Pharmaceuticals, personal fees from Alkem Metabolomics, outside the submitted work; and Director GCTP Ltd. **Dr. Lam** is supported by a Clinician Scientist Award from the National Medical Research Council of Singapore; has Received research support from Novo Nordisk and Roche Diagnostics; has Served as consultant or on the Advisory Board/ Steering Committee/ Executive Committee for Alleviant Medical, Allysta Pharma, AnaCardio AB, Applied Therapeutics, AstraZeneca, Bayer, Bioeuetics, Boehringer Ingelheim, Boston Scientific, Bristol Myers Squibb, CardioRenal, CPC Clinical Research, Eli Lilly, Impulse Dynamics, Intellia Therapeutics, Ionis Pharmaceutical, Janssen Research & Development LLC, Medscape/WebMD Global LLC, Merck, Novartis, Novo Nordisk, Prosciento Inc, Quidel Corporation, Radcliffe Group Ltd., Recardio Inc, ReCor Medical, Roche Diagnostics, Sanofi, Siemens Healthcare Diagnostics and Us2.ai; and serves as Co-founder & non-executive director of Us2.ai. **Dr. Pfeffer** reports research grant support (via institution) from Lexicon and Novartis; is a consultant to Alnylam, Apnimed, AstraZeneca, Boehringer Ingelheim and Eli Lilly Alliance, DalCor, Intellia, NHLBI CONNECTs (Master Protocol Committee), Novartis, and Novo Nordisk, and equity in DalCor. **Dr. Pitt** has served as a consultant for Bayer, AstraZeneca, Bristol Meyers Squibb, Boehringer Ingelheim, Lexicon, Anacardia, and G3 Pharmaceuticvals. He has served as a consultant and received stock options or stocks from Sea Star Medical, Vifor, Scpharmaceuticals, SQinnovations, KBP Biosciences, Sarfez, Cereno Scientific, Prointel, and Brainstorm Medical. He holds a US Patent (9931412-site specific delivery of Eplerenone to the myocardium) and has a US Patent pending (63/045,783 Histone Modulating agents for the prevention and treatment of organ damage). **Dr. Zannad** reports personal fees from steering committee fees, during the conduct of the study; personal fees from Boehringer, personal fees from BMS, personal fees from CVRx, personal fees from Cardior, personal fees from Cereno, personal fees from Cellprothera, personal fees from Merck, personal fees from Owkin, personal fees from Roche, personal fees from Northsea, outside the submitted work; and stock options at G3Pharmaceutical and equities at Cereno, Cardiorenal, Eshmoun Clinical research and founder of CVCT. **Dr. Zile** reports research funding from Novartis and consulting for Novartis, Abbott, Boston Scientific, CVRx, EBR, Endotronix, Ironwood, Merck, Medtronic, and Myokardia V Wave. **Dr. McMurray** reports payments to his employer Glasgow University, from Bayer time spent as co-principal investigator of the FINEARTS trial with finerenone. These payments were made through a Consultancy with Glasgow University and I have not received personal payments in relation to these trials/drugs from Bayer, during the conduct of the study; other from AstraZeneca, other from Amgen, other from Cardurion, other from Cytokinetics, other from Glaxo Smith Kline, other from KBP Biosciences, other from Novartis, personal fees from
George Clinical PTY Ltd., personal fees from Abbott, Alkem Metabolics, AstraZeneca, Blue
Ocean Scientific Solutions Ltd., Boehringer Ingelheim, Canadian Medical and Surgical
Knowledge, Emcure Pharmaceuticals Ltd., Eris Lifesciences, European Academy of CME,
Hikma Pharmaceuticals, Imagica Health, Intas Pharmaceuticals, J.B. Chemicals &
Pharmaceuticals Ltd., Lupin Pharmaceuticals, Medscape/Heart.Org., ProAdWise
Communications, Radcliffe Cardiology, Sun Pharmaceuticals, The Corpus, Translation Research
Group, Translational Medicine Academy, personal fees from Global Clinical Trial Partners Ltd.,
personal fees from Alnylam Pharmaceuticals, Bayer, BMS, Ionis Pharmaceuticals, Novartis,
Regeneron Pharmaceuticals, River 2 Renal Corp., outside the submitted work. **Dr. Solomon** has
received research grants from Alexion, Alnylam, AstraZeneca, Bellerophon, Bayer, BMS, Boston
Scientific, Cytokinetics, Edgewise, Eidos, Gossamer, GSK, Ionis, Eli Lilly, MyoKardia,
NIH/NHLBI, Novartis, Novo Nordisk, Respicardia, Sanofi Pasteur, Theracos, US2.AI and has
consulted for Abbott, Action, Akros, Alexion, Alnylam, Amgen, Arena, AstraZeneca, Bayer,
Boehringer-Ingelheim, BMS, Cardior, Cardurion, Corvia, Cytokinetics, Daiichi-Sankyo, GSK,
Lilly, Merck, Myokardia, Novartis, Roche, Theracos, Quantum Genomics, Janssen, Cardiac
Dimensions, Tenaya, Sanofi-Pasteur, Dinaqor, Tremeau, CellProThera, Moderna, American
Regent, Sarepta, Lexicon, Anacardio, Akros, Valo. **Dr. Vaduganathan** has received research
grant support, served on advisory boards, or had speaker engagements with Alnylam
Pharmaceuticals, American Regent, Amgen, AstraZeneca, Bayer AG, Baxter Healthcare, BMS,
Boehringer Ingelheim, Chiesi, Cytokinetics, Esperion, Fresenius Medical Care, Idorsia
Pharmaceuticals, Lexicon Pharmaceuticals, Merck, Milestone Pharmaceuticals, Novartis, Novo
Nordisk, Pharmacosmos, Recordati, Relypsa, Roche Diagnostics, Sanofi, and Tricog Health, and
participates on clinical trial committees for studies sponsored by Amgen, AstraZeneca, Galmed,
Novartis, Bayer AG, Occlutech, Pharmacosmos, and Impulse Dynamics.
**Abstract**

**Background:** Natriuretic peptides are the primary biomarkers recommended in heart failure (HF) guidelines to risk stratify patients in clinical practice and serve as key eligibility criteria in contemporary clinical trials. However, threshold levels typically do not account for measures of adiposity, such as body mass index (BMI).

**Objective:** To evaluate the association between N-terminal pro-B-type natriuretic peptide (NT-proBNP) with clinical outcomes in individuals with HF and mildly reduced or preserved ejection fraction (HFmrEF/HFpEF), stratified according to BMI.

**Methods:** In this participant-level pooled analysis of 4 global, randomized, outcomes trials including adults with HFmrEF/HFpEF, the association between NT-proBNP and clinical outcomes (cardiovascular death or HF hospitalization, cardiovascular death, HF hospitalization, and all-cause death) was evaluated according to BMI as a continuous and categorical variable.

**Results:** Among 14,750 participants (mean age, 72±9 years; 50% female; mean BMI, 30±6 kg/m²; median NT-proBNP, 836 pg/mL), higher baseline BMI was significantly and non-linearly associated with lower NT-proBNP levels. Over a median follow-up of 2.8 years, each doubling of baseline NT-proBNP was associated with a 40% higher covariate-adjusted rate of cardiovascular death or HF hospitalization (hazard ratio, 1.40; 95% CI, 1.36-1.43; *P*<0.001). However, this association appeared incrementally blunted with higher baseline BMI (*P*<0.001). For the same absolute risk of cardiovascular death or HF hospitalization (5 events per 100 person-years), NT-proBNP levels in participants without atrial fibrillation were nearly 3-fold lower among those with BMI≥35 kg/m² (158 pg/mL) vs. <35 kg/m² (450 pg/mL). At a contemporary NT-proBNP-based trial eligibility threshold, absolute risk of cardiovascular death or HF hospitalization ranged from 3.5 per 100 person-years among persons with BMI <30 kg/m² to 7.3 per 100 person-years among those with BMI≥40 kg/m².

**Conclusions:** In this analysis, current NT-proBNP thresholds substantially underestimated the absolute risk of adverse HF outcomes among persons with higher BMI. These data question single fixed thresholds and instead suggest that lower NT-proBNP cutoffs may more appropriately risk stratify patients with higher BMI.

**Keywords:** heart failure; obesity; natriuretic peptides; outcomes; heart failure with preserved ejection fraction; clinical trials

**Clinical Trial Registration:** I-Preserve (NCT00095238); TOPCAT (NCT00094302); PARAGON-HF (NCT01920711); DELIVER (NCT03619213)
Abbreviations and Acronyms

<table><tr><td>AF</td><td>Atrial fibrillation</td></tr><tr><td>BMI</td><td>Body mass index</td></tr><tr><td>HFmrEF</td><td>Heart failure with mildly reduced ejection fraction</td></tr><tr><td>HFpEF</td><td>Heart failure with preserved ejection fraction</td></tr><tr><td>NP</td><td>Natriuretic peptide</td></tr><tr><td>NT-proBNP</td><td>N-terminal prohormone of B-type natriuretic peptide</td></tr></table>
Introduction

Obesity is heterogeneous and progressive chronic disease forecasted to impact more than 1.5 billion persons worldwide by 2035,¹ and is a leading risk factor for the onset and progression of heart failure (HF),²,³ particularly HF with preserved ejection fraction (HFpEF).⁴ In recent clinical trials and observational studies,²,⁵,⁶ the prevalence of overweight or obesity among individuals with HFpEF has exceeded 75%, emphasizing the need for robust HF risk stratification approaches across the clinical spectrum of body mass index (BMI).

Natriuretic peptides (NPs), such as N-terminal pro-B-type natriuretic peptide (NT-proBNP), are guideline-recommended to ascertain the presence and severity of HF, and can additionally inform optimization of guideline-directed medical therapies.⁷,⁸ As such, NP levels are widely measured in clinical practice in individuals with established HF. However, well-recognized challenges relating to interpretation of NP levels in persons with obesity may disproportionately confound detection of disease progression, as well as shared discussions around prognosis and management, in this sizeable, growing, and high-risk population.

NP levels in individuals with obesity are typically lower compared with those with BMI <25 kg/m²,⁹ reflecting the complex and bidirectional relationship between NPs and body composition. Higher NP levels are associated with greater lipolytic activity,¹⁰ and therein a more favorable adipose tissue distribution and cardiometabolic profile.¹¹ Therefore, lower NP levels among individuals with HF and obesity may reflect reverse causation (i.e., a “natriuretic handicap”).⁹ Further, obesity and its complications (e.g., excess epicardial adipose tissue and other metabolic factors) may attenuate NP release (e.g., through enhanced pericardial restraint),¹²⁻¹⁴ impair NP processing,¹⁵,¹⁶ and/or enhance NP clearance (e.g., through skeletal muscle, which is often increased among individuals with obesity).¹⁷⁻²¹

The expanding prevalence of HF and obesity,¹,²²,²³ including class III obesity (BMI ≥40 kg/m²),²⁴ coupled with the widespread use of NPs, underscores the need to improve understanding of the prognostic utility of NPs across the spectrum of BMI. However, owing to sample size limitations, BMI-based exclusion criteria, and/or other factors, prior studies evaluating the association between NPs and overweight/obesity have been restricted to narrow BMI ranges.²⁵⁻²⁸
As such, larger studies evaluating a wider range of BMI may ameliorate persistent evidence
gaps, with potentially important implications for clinical and research efforts. In this participant-
level pooled analysis of 4 large-scale randomized trials including individuals with HF with
mildly reduced ejection fraction (HFmrEF) and HFpEF, we evaluated the relationship between
NT-proBNP, BMI, and clinical outcomes.

Methods

**Patient Population, Trial Characteristics, and Trial Procedures**

Individual participant-level data from I-Preserve (Irbesartan in Heart Failure and Preserved Ejection Fraction),²⁹ TOPCAT (Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist),³⁰ PARAGON-HF (Prospective Comparison of Angiotensin Receptor-Neprilysin Inhibitor with Angiotensin Receptor Blocker Global Outcomes in HF with Preserved Ejection Fraction),³¹ and DELIVER (Dapagliflozin Evaluation to Improve the Lives of Patients With Preserved Ejection Fraction Heart Failure) trials were included in the analysis.³² Details of the design and baseline characteristics of each trial have been previously reported.²⁹⁻³⁵

In brief, I-Preserve, TOPCAT, and PARAGON-HF recruited individuals with HF and left ventricular ejection fraction (LVEF) ≥45%, while DELIVER recruited individuals with HF and LVEF >40%. Trial participants were randomized to irbesartan (I-Preserve), spironolactone (TOPCAT), dapagliflozin (DELIVER), or matching placebo. In PARAGON-HF, participants were randomized to sacubitril/valsartan or valsartan after a single-blind run-in phase in which participants were treated sequentially with half-target doses of both study medications.

Participant-level data from TOPCAT were restricted to those enrolled in the Americas (United States, Canada, Brazil, and Argentina), given established regional heterogeneity observed for study drug urine metabolites and trial endpoints.³⁶,³⁷ Median follow-up ranged from 27.6 months in DELIVER to 49.5 months in I-Preserve. Independent ethics committees or institutional review boards approved each trial protocol at each study center. All participants provided written informed consent.

Eligibility criteria relating to BMI and NPs varied across the trials (Supplementary Table 1).
While I-Preserve and TOPCAT did not have BMI-based exclusion criteria, BMI >40 kg/m² and
>50 kg/m² were exclusionary in PARAGON-HF and DELIVER, respectively.³¹,³² NP-based eligibility criteria were included in TOPCAT, PARAGON-HF, and DELIVER, but not I-Preserve. Participants in TOPCAT were enrolled based on HF hospitalization within the 12 months preceding randomization or elevated NPs (NT-proBNP ≥360 pg/mL or BNP ≥100 pg/mL) within 60 days of randomization.³⁰ In PARAGON-HF, participants without atrial fibrillation (AF) were required to have NT-proBNP >300 pg/mL (>200 pg/mL if HF hospitalization within 9 months of the screening visit), while those with AF were required to have NT-proBNP >900 pg/mL (>600 pg/mL if HF hospitalization within 9 months of the screening visit).³¹ In DELIVER, participants without AF were required to have NT-proBNP ≥300 pg/mL, while those with AF were required to have NT-proBNP ≥600 pg/mL.³²

## Assessment of Body Mass Index and NT-proBNP

Trial participants with complete data for BMI (≥18.5 kg/m²) and NT-proBNP were included in this analysis. Body weight was measured to the nearest 0.1 kg at screening with participants in light clothing, without shoes. BMI was calculated as body weight (in kg) divided by height (in m²). In I-Preserve, PARAGON-HF, and DELIVER, NT-proBNP levels were measured in a central trial laboratory using sandwich immunoassay on an Elecsys® platform (Roche Diagnostics).²⁸,³⁸,³⁹ In TOPCAT, NT-proBNP levels were measured in local laboratories at participating sites.²⁷,⁴⁰ Given the skewed distribution of NT-proBNP, all values were log-transformed prior to analysis.

## Study Outcomes

The primary outcome in this analysis was cardiovascular (CV) death or HF hospitalization. Other outcomes included HF hospitalization, CV death, and all-cause death. All HF and mortality outcomes were independently adjudicated by blinded expert committees.

## Statistical Analysis

Baseline characteristics of participants were cross-tabulated across BMI categories (18.5 to <25, 25 to <30, 30 to <35, 35 to <40, and ≥40 kg/m²). The association between baseline BMI and NT-proBNP was evaluated using restricted cubic splines with the number of knots (placed according to Harrell's recommended percentiles) selected to optimize the Akaike information criteria,
estimated through multivariable linear regression. Models were adjusted for trial, randomized treatment, age, sex, self-reported race, history of AF, estimated glomerular filtration rate (eGFR), systolic blood pressure, LVEF, and diuretic use at baseline. Given prior evidence demonstrating non-linear associations with clinical outcomes,⁴¹,⁴² eGFR and systolic blood pressure were a priori fitted using cubic splines with 3 knots (placed at Harrell's recommended percentiles). As the association between BMI and NT-proBNP was found to be non-linear, we then separately examined the association between BMI and NT-proBNP in each BMI category.

Associations between NT-proBNP and clinical outcomes according to BMI category were assessed using multivariable Cox proportional hazards regression models, adjusted for the aforementioned covariates. Similar to a prior study,⁴³ we log-transformed NT-proBNP using a base-2 logarithm with 500 pg/mL as the reference value to estimate hazard ratios (HRs) with 95% CI per doubling of NT-proBNP. Model output was displayed using restricted cubic splines, with the number of knots selected to optimize the Akaike information criteria.

The proportional hazards assumption was assessed using Schoenfeld residuals and log-log plots. Of note, violation of the proportional hazards assumption was identified, with non-parallel hazard functions for some of the BMI categories noted early within the follow-up period. To evaluate the impact of the observed proportionality violation(s), alternative Cox proportional hazards models were constructed with iterative landmarking at 7-day intervals. This process revealed 147 days (21 weeks) to be the earliest timepoint at which no proportionality violations were observed. Models landmarked at 147 days provided similar point estimates (and 95% CI) compared with the original (non-landmarked) models **(Supplementary Table 2)**. As such, the findings reported herein reflect the results of the original models.

To evaluate absolute risk associated with specific NT-proBNP levels across the evaluated range of BMI, Poisson regression was used to compare the equivalent NT-proBNP concentrations corresponding to specific rates of clinical events across BMI categories. Consistent with a prior analysis,⁴³ unadjusted event rates of 5 and 10 per 100 person-years were selected for illustrative purposes; these rates are commonly considered in HF trial power calculations. Uncertainty intervals (UIs) were constructed, representing NT-proBNP concentrations at the upper and lower
bounds of the 95% CI of the event rate. To further contextualize absolute risk of clinical
outcomes according to BMI category, Poisson regression was used to estimate incidence rates of
CV death or HF hospitalization for each BMI category at NT-proBNP eligibility thresholds
recently applied in clinical trials (300 pg/mL in individuals without AF and 600 pg/mL in
individuals with AF). Poisson regression was additionally used to estimate incidence rates of
each outcome across the continuous ranges of BMI and NT-proBNP, with findings displayed as
contour plots. Statistical analyses were conducted using Stata, version 18.5 (StataCorp; College
Station, TX), and two-sided P values <0.05 were considered statistically significant.

Sensitivity and Supplementary Analyses

Multiple *post hoc* sensitivity and supplementary analyses were performed to evaluate the
robustness and enhance the translatability of the study findings. First, to assess the potential
influence of NT-proBNP assay heterogeneity, key analyses were repeated after exclusion of
TOPCAT-Americas. Second, key analyses were repeated using alternative specifications for
eGFR and blood pressure (included as linear [rather than spline] terms). Third, Fine-Gray
subdistribution hazard models were used to assess the potential impact of competing risks of
death. Fourth, key analyses were repeated using alternative BMI thresholds (e.g., <30 kg/m², ≥30
to <35 kg/m², and ≥35 kg/m²). Fifth, rates of clinical outcomes were estimated at alternative
BMI-based NT-proBNP thresholds (500 pg/mL if BMI <35 kg/m²; 220 pg/mL if BMI ≥35
kg/m²) recently proposed to enhance HFpEF diagnosis in persons with unexplained dyspnea.⁴⁴

Results

Patient Population

Overall, 14,750 participants (mean age, 72 ± 9 years; 50.3% female; mean BMI, 30.0 ± 5.6 kg/m²; BMI range, 18.5 to 69.6 kg/m²; median NT-proBNP, 836 [423, 1557] pg/mL; 48.0% with history of AF) across the 4 trials had complete data for BMI (≥18.5 kg/m²) and NT-proBNP.

Participants with higher baseline BMI were more likely to be younger, female, and have self-reported White or Black race, higher systolic blood pressure, greater symptoms and functional limitations, and a history of hypertension, diabetes, and AF (Table 1).
Despite younger age, eGFR values were similar between individuals with BMI $\ge$40 kg/m$^2$ versus 18.5 to <25 kg/m$^2$. In addition, participants with higher BMI at baseline were generally more likely to have background use of angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers, β-blockers, and diuretics. However, higher BMI was also associated with lower prevalences of Asian race, prior stroke, and prior myocardial infarction. The participant-level distribution of baseline NT-proBNP across the range of BMI included in the analysis is displayed in **Supplementary Figure 1**.

## Association Between BMI and NT-proBNP at Baseline

Geometric mean NT-proBNP levels generally decreased with higher baseline BMI category (Central Illustration and Figure 1), such that participants with BMI $\ge$40 kg/m$^2$ had a baseline geometric mean NT-proBNP level ~25% lower than those with BMI 18.5 to <25 kg/m$^2$. When examined as continuous variables, BMI was significantly (overall *P* value <0.001) and non-linearly (*P* value for non-linearity <0.001) associated with lower NT-proBNP; steeper increments in baseline mean NT-proBNP were observed with lower compared with higher BMI (Figure 2). Associations between baseline NT-proBNP and BMI according to age category (*P*$_{interaction}$=0.56), sex (*P*$_{interaction}$=0.26), race (*P*$_{interaction}$=0.05), and history of AF (*P*$_{interaction}$=0.005) are displayed in **Supplementary Figures 2 and 3**. Overall, NT-proBNP values appeared highest among older adults, males, self-reported Black participants, and in those with AF.

## Rates of Clinical Outcomes per Doubling of NT-proBNP, by BMI Category

Over a median [IQR] follow-up of 2.8 [2.2, 3.5] years, 3,069 participants experienced CV death or HF hospitalization, 2,175 experienced HF hospitalization, 1,443 experienced CV death, and 2,482 experienced all-cause death.

In fully adjusted models, each doubling of baseline NT-proBNP was associated with a 40% higher rate of CV death or HF hospitalization (adjusted hazard ratio [aHR], 1.40; 95% CI, 1.36 to 1.43; *P*<0.001). Similar patterns were observed for HF hospitalization (aHR, 1.39; 95% CI, 1.34 to 1.43), CV death (aHR, 1.47; 95% CI, 1.41 to 1.53), and all-cause death (aHR, 1.39; 95% CI, 1.34 to 1.43) (Table 2).
Higher baseline NT-proBNP concentrations were associated with adverse clinical outcomes in all BMI categories (Central Illustration, Table 2 and Figure 3). However, evidence of effect modification was observed for CV death or HF hospitalization ($P_{interaction}=0.008$), characterized by incremental blunting of the association between each doubling of baseline NT-proBNP and outcomes with higher BMI. As such, spread of risk between the BMI categories was highest at lower baseline NT-proBNP concentrations, and lowest at higher NT-proBNP concentrations (Figure 3). Similar findings were observed for HF hospitalization ($P_{interaction}=0.004$), but no strong evidence of effect modification was observed for the mortality outcomes. Relative rates of adverse outcomes, for any given level of NT-proBNP, generally appeared greatest among those with $BMI \ge 40 \text{ kg/m}^2$ (Figure 3).

Sensitivity analyses excluding TOPCAT-Americas (Supplementary Table 3 and Supplementary Figure 4), evaluating alternative linear specifications for eGFR and systolic blood pressure (Supplementary Table 4), and considering competing risks of death (Supplementary Table 5) produced similar findings as compared with the main analysis. Analysis of alternative BMI subgroups additionally revealed similar associations (Supplementary Table 6 and Supplementary Figure 5).

## Incidence Rates of Clinical Outcomes Across the Range of NT-proBNP, by BMI

At any given level of baseline NT-proBNP (especially with lower NT-proBNP values), incidence rates of CV death or HF hospitalization, as well as HF hospitalization, increased incrementally with higher BMI (Figure 4). However, these patterns of association appeared blunted for mortality outcomes (Figure 4). Conversely, for any given level of BMI, incidence rates of clinical outcomes increased with higher baseline NT-proBNP, including among those with and without AF (Supplementary Figure 6).

Among participants without a history of AF, baseline NT-proBNP concentrations corresponding to specific incidence rates of clinical outcomes, stratified by BMI category, are displayed in Table 3. For those with $BMI \ge 40 \text{ kg/m}^2$, an NT-proBNP level of 155 pg/mL corresponded to an absolute risk of CV death or HF hospitalization of 5 per 100 person-years. Corresponding NT-proBNP levels were 158 pg/mL, 372 pg/mL, 502 pg/mL, and 484 pg/mL for participants with
BMI 35 to <40 kg/m², BMI 30 to <35 kg/m², BMI 25 to <30 kg/m², and BMI 18.5 to <25 kg/m², respectively, reflecting a more than 3-fold difference in NT-proBNP between the lowest and highest BMI categories for the same absolute risk. Similar patterns were observed for an incidence rate of 10 per 100 person-years and for other outcomes. However, the gradient of NT-proBNP across BMI categories for each level of absolute risk was shallower for mortality outcomes.

Similar findings were observed in a sensitivity analysis exploring participants with baseline BMI $≥35$ kg/m² vs. <35 kg/m² (**Supplementary Table 7**). NT-proBNP values corresponding to an CV death or HF hospitalization event rate of 5 per 100 person-years were nearly 3-fold lower among participants with BMI $≥35$ kg/m² (158 pg/mL; UI, 103 to 242 pg/mL) vs. <35 kg/m² (450 pg/mL; UI, 401 to 505 pg/mL). NT-proBNP values corresponding to an event rate of 10 per 100 person-years were approximately 2-fold lower among participants with BMI $≥35$ kg/m² (744 pg/mL; UI, 569 to 972 pg/mL) vs. <35 kg/m² (1408 pg/mL; UI, 1271 to 1559 pg/mL).

## Incidence Rates of Clinical Outcomes at Recent Trial NT-proBNP Eligibility Thresholds, by BMI Category

Among pooled trial participants without history of AF, predicted incidence rates (per 100 person-years) at NT-proBNP = 300 pg/mL increased substantially with higher BMI category, such that participants with BMI $≥40$ kg/m² had a ≥2-fold higher predicted rate of CV death or HF hospitalization (IR, 7.3 per 100 person-years) compared with participants with BMI 18.5 to <25 kg/m² (IR, 3.5 per 100 person-years) (**Central Illustration** and **Figure 5**). These findings appeared to be primarily driven by a steep gradient of risk for HF hospitalization with higher BMI at this NT-proBNP threshold (**Supplementary Figures 7-8**); participants with BMI $≥40$ kg/m² had a 3-fold higher predicted rate of HF hospitalization (IR, 6.0 per 100 person-years) compared with participants with BMI 18.5 to <25 kg/m² (IR, 2.0 per 100 person-years). Similar findings were observed when alternative BMI subgroups were examined (**Supplementary Figure 9**).

The associations between clinical outcomes and BMI category at NT-proBNP = 600 pg/mL appeared blunted among participants with history of AF at baseline, who exhibited uniformly
higher event rates across the BMI spectrum (Figure 5 and Supplementary Figures 7-8).

However, in a sensitivity analysis restricted to I-Preserve and TOPCAT-Americas (Supplementary Figure 10), as these trials did not require specific NT-proBNP values for entry, participants with BMI ≥40 kg/m² exhibited the highest predicted rate of CV death or HF hospitalization at this NT-proBNP threshold (IR, 16.3 per 100 person-years), which was ~50-60% higher compared with the other BMI subgroups.

## Incidence Rates of Clinical Outcomes at Recently Proposed BMI-Based NT-proBNP Rule-In Thresholds for HFpEF Diagnosis, by BMI Category

The estimated rate of CV death or HF hospitalization appeared similar-to-slightly higher for participants with BMI ≥35 kg/m² (at NT-proBNP = 220 pg/mL) when compared with participants with BMI <35 kg/m² (at NT-proBNP = 500 pg/mL) (IR, 6.0 [95% CI, 5.1 to 7.0] vs. 5.4 [95% CI, 5.0 to 5.7]) (Supplementary Figure 11). This appeared to be driven by a higher threshold-specific rate of HF hospitalization, but similar-to-slightly lower rate of CV death, among those with BMI ≥35 kg/m² vs. <35 kg/m².

## Discussion

In this participant-level pooled analysis of 4 large-scale HFmrEF/HFpEF outcomes trials evaluating the interplay between NT-proBNP and clinical outcomes across a wide spectrum of BMI (18.5 to >50 kg/m²), baseline NT-proBNP levels were significantly and non-linearly associated with BMI. Namely, NT-proBNP levels increased steeply with lower BMI, and declined gradually from BMI 30 to 50 kg/m², but with significant differences according to age, sex, race, and AF status. Higher baseline NT-proBNP concentrations were associated with increased risk of adverse outcomes in all BMI categories. However, at any given NT-proBNP concentration (including NT-proBNP thresholds recently used in clinical trials), individuals with higher BMI experienced higher risk of CV death or HF hospitalization. Similarly, at specific levels of absolute risk of CV death or HF hospitalization, participants with higher BMI exhibited up to 3-fold lower NT-proBNP concentrations when compared to those with lower BMI. Taken together, these findings enhance understanding of the association between NPs, BMI, and clinical outcomes in individuals with HFmrEF/HFpEF, and underscore the importance of tailoring NP interpretation to the broad dynamic range of BMI.
Despite BMI-based exclusion criteria in 2 of the 4 trials, ~1 in 5 individuals with HFmrEF/HFpEF in this analysis had BMI ≥35 kg/m². This finding underscores the high and increasing prevalence of more severe forms of obesity at population levels,²⁴ including among persons with HFpEF. However, while obesity is associated with lower NP levels in individuals with or without HF, individuals with higher levels of BMI – who may exhibit more dysfunctional NP biology – have been relatively understudied. In a small (n=89) exploratory study of the ROPA-DOP (Randomized Evaluation of Heart Failure With Preserved Ejection Fraction Patients With Acute Heart Failure and Dopamine) trial, participants with BMI ≥40 kg/m² hospitalized with acute HFpEF had admission NT-proBNP values nearly 4-fold lower compared with BMI <30 kg/m², and ~2.5-fold lower compared with BMI 30 to 39.9 kg/m².⁴⁵ This analysis considerably extends these prior observations. Indeed, in this broad population of individuals with HFmrEF/HFpEF in stable ambulatory care and with predominantly mild symptoms, BMI ≥40 kg/m² was associated with markedly lower NT-proBNP levels even when compared to BMI 30 to <35 kg/m², despite equivalent levels of absolute risk for each outcome.

Baseline BMI was significantly and non-linearly associated with baseline NT-proBNP in this analysis, with sharply higher concentrations at lower BMI (<30 kg/m²) and more modest declines with BMI >30 kg/m². This profile may offer unique and mechanistically informative insights concerning NP biology in HFmrEF/HFpEF. First, these patterns may reflect some level of reverse causation (i.e., lower BMI due to higher NP levels).¹¹ However, older adults with HFmrEF/HFpEF have been shown to have higher NP levels (as observed herein) and higher risks of HF progression.²⁷ This duality has traditionally been considered to reflect more advanced HF, but the more favorable NYHA functional class and lower use of key cardiovascular therapies in this subpopulation with lower BMI (but higher NT-proBNP levels) highlights the potential for other drivers, such as body composition. Indeed, skeletal muscle mass, which is often diminished among older adults, plays an important role in NP clearance.¹⁸ In the Dallas Heart Study, NT-proBNP concentrations were more closely associated with lean mass than with fat mass.¹⁷,¹⁹ As such, elevated NPs may also be a marker of sarcopenia and frailty, emphasizing the importance of considering body composition, in addition to BMI, in NP interpretation. Alternatively, the blunting of the association between BMI and NT-proBNP at BMI levels >30 kg/m² may imply a
threshold effect of excess adiposity on NP biology in HFmrEF/HFpEF. Such a threshold effect may derive from impaired NP release due to enhanced pericardial restraint, which has been especially observed in persons with HFpEF and BMI $\ge 35$ kg/m$^2$.¹² This discordance between disease status and NP levels with higher BMI may additionally explain the observed mild-to-moderate blunting of NT-proBNP-outcome associations with higher BMI category.

These findings may have important implications for clinical and research efforts involving individuals with HF. Namely, population aging and expanding prevalence of upstream root causes of HF, such as obesity and interrelated metabolic risk factors,¹,²²,⁴⁶ have brought HF prevention into sharp focus. The success of such efforts may hinge on accurate and unbiased identification of individuals at highest risk.⁴⁷ In this context, some groups, such as the American Diabetes Association, have recommended NP-based screening and management to guide HF prevention efforts.⁴⁸ However, if the recommended threshold NT-proBNP level of $\ge 125$ pg/mL⁴⁸ is broadly implemented without explicit consideration of BMI, such recommendations may disproportionately impair HF diagnosis and prevention efforts in individuals with higher BMI, who are often at highest risk for incident HF.⁴ Indeed, many individuals with established HFmrEF/HFpEF in this analysis (e.g., BMI $\ge 35$ kg/m$^2$) exhibited NT-proBNP values near this normal range, which were associated with high absolute risk of HF and mortality events. To ameliorate potential NP-based biases in clinical care, there is need for more explicit guidance around incorporating BMI into NP interpretation.

However, the landscape is shifting. In a recent analysis of adults with chronic unexplained dyspnea, contemporary guideline-based NT-proBNP rule-in criteria exhibited limited sensitivity for HFpEF diagnosis among persons with BMI-defined obesity, especially those with BMI $\ge 35$ kg/m$^2$.⁴⁴ Analogously, our findings suggest current thresholds may perform poorly for prognostication once HFpEF is established, especially among individuals with BMI $\ge 35$ kg/m$^2$. While the associational insights in this analysis should be considered hypothesis-generating, the combination of these findings underscore the potential of BMI-tailored NP thresholds in the care of persons with suspected or established HFpEF. BMI-tailored rule-in thresholds of $\ge 500$ pg/mL for persons with BMI <35 kg/m$^2$ and $\ge 220$ pg/mL for persons with BMI $\ge 35$ kg/m$^2$ have been recently proposed on the basis of improved diagnostic performance.⁴⁴ Adaptation of these
proposed thresholds in this analysis revealed comparable rates of clinical events, albeit with a
higher predicted rate of HF events among participants with BMI $\ge$35 kg/m$^2$ even at the lower
NT-proBNP threshold of 220 pg/mL. Taken together, although recognition of the wide range of
contributors to circulating NT-proBNP is recommended to enhance individualized interpretation,
BMI = 35 kg/m$^2$ may represent a pragmatic and biologically relevant threshold around which to
develop and validate NT-proBNP thresholds that might inform HF diagnosis, prognosis, and
management. Ultimately, data from external cohorts and/or prospective studies are needed to
more rigorously establish BMI-based thresholds in HF care.

This analysis also provides implications for the design of clinical trials. Thus far, large-scale HF outcomes trials have generally not considered BMI when implementing NP-based inclusion criteria, possibly leading to BMI-based selection bias in trial enrollment. Indeed, individuals with BMI $\ge$40 kg/m$^2$ in this analysis exhibited twice the absolute risk of those with BMI <30 kg/m$^2$ at recent NT-proBNP based trial eligibility thresholds. Given the widespread and expanding prevalence of obesity, this analysis suggests adopting less stringent NP-based eligibility criteria for individuals with higher BMI may enhance recruitment without adversely impacting HF event rates (however CV death rates might be lower). Some interventional trials (NCT01626079, NCT03499236, NCT05064709) in HF have already implemented BMI-tailored NP-based eligibility criteria. Given the marked gradient of risk observed across BMI for those without but not with AF, tailoring of NP-based entry criteria to BMI may be most relevant for persons without AF. Using a combination of NP-based and non-NP-based enrichment strategies, such as minimum thresholds for exercise function combined with other criteria (e.g., abnormal cardiac structure and function or other evidence of elevated filling pressures), as recently implemented in the SUMMIT (Study of Tirzepatide in Participants With HFpEF and Obesity) trial (overall trial median NT-proBNP <200 pg/mL),⁴⁹ may represent another approach to ease recruitment and expand generalizability to individuals with HFmrEF/HFpEF and obesity.

## Limitations

While this analysis of 4 complementary trials provides comprehensive insights into the interplay
between NT-proBNP and adjudicated clinical outcomes in HFmrEF/HFpEF across a wide range
of BMI, several key limitations should be emphasized. First, the BMI-based exclusion criteria
employed in PARAGON-HF and DELIVER may limit the generalizability of these findings to some individuals with higher BMI, especially BMI >50 kg/m². Similarly, the use of NP-based eligibility criteria in 3 of the trials may have reduced representation of lower-risk individuals with HFmrEF/HFpEF at higher BMI levels. Second, despite careful adjustment for covariates known to impact NT-proBNP levels and outcomes, residual confounding may have influenced the findings of this study. Third, while BMI remains widely used in clinical care and research, the emergence of non-BMI-centric obesity definitions underscores the need for studies exploring the interplay between NPs and other adiposity-related anthropometrics. Finally, further efforts are needed to ascertain whether these findings apply to individuals with HF with reduced ejection fraction or more advanced kidney dysfunction, to community settings, and to individuals with more diverse racial and ethnic backgrounds.

## Conclusion

In this participant-level pooled analysis of 4 international HFmrEF/HFpEF outcomes trials, higher BMI was associated with higher absolute risk of CV death or HF hospitalization for any given level of NT-proBNP, with the steepest gradient of risk observed for individuals with BMI ≥40 kg/m². These findings underscore the importance of tailoring interpretation of NP levels to the broad dynamic range of BMI, rather than the presence or absence of obesity alone, in clinical and research efforts involving individuals with HFmrEF/HFpEF.
**Acknowledgements:** None

**Data Availability:**

Data underlying the findings described in this manuscript may be obtained in accordance with the data sharing policy of each of the trial sponsors (outlined below). The data sharing policy of Bristol-Myers Squibb is detailed at https://www.bms.com/researchers-and-partners/independent-research/data-sharing-request-process.html. TOPCAT data may be requested via the Biologic Specimen and Data Repository Information Coordinating Center of the National Heart, Lung, and Blood Institute of the National Institutes of Health (https://biolinc.c.nhlbi.nih.gov/studies/topcat/). Novartis's data sharing policy is reviewed at https://www.novartis.com/clinicaltrials/transparency. AstraZeneca's data sharing policy is described at https://www.astrazenecaclinicaltrials.com/our-transparency-commitments/. Data for studies directly listed on Vivli can be requested through Vivli at www.vivli.org. Data for studies not listed on Vivli could be requested through Vivli at https://vivli.org/members/enquiries-about-studies-not-listed-on-the-vivli-platform/. AstraZeneca's Vivli member page is also available outlining further details: https://vivli.org/ourmember/astrazeneca/.

**Funding:** I-Preserve was sponsored by Bristol-Myers Squibb and Sanofi-Aventis, TOPCAT was sponsored by the National Heart, Lung, and Blood Institute of the National Institutes of Health, PARAGON-HF was sponsored by Novartis, and DELIVER was sponsored by AstraZeneca.
**Perspectives**

**Competency in Patient Care**

In this participant-level pooled analysis of 4 large-scale HFmrEF/HFpEF trials, higher baseline NT-proBNP was associated with HF and mortality outcomes in all BMI categories. However, at specified NT-proBNP thresholds, absolute risk of HF events was up to 3-fold higher in persons with elevated compared with non-elevated BMI. Similarly, at specified levels of absolute risk of HF events, baseline NT-proBNP values were up to 3-fold lower in persons with elevated compared with non-elevated BMI.

**Translational Outlook**

These findings suggest single fixed NT-proBNP thresholds may substantially underestimate absolute risk of adverse HF outcomes among persons with higher BMI. As such, BMI-tailored NT-proBNP cutoffs in established HFpEF may enhance clinical care and research efforts, but further validation efforts are needed.
References

1. World Obesity Federation. World Obesity Atlas 2024. London: World Obesity Federation, 2024. https://data.worldobesity.org/publications/?cat=22. Accessed December 2, 2024.

2. Adamson C, Kondo T, Jhund PS, et al. Dapagliflozin for Heart Failure According to Body Mass Index: The DELIVER Trial. *Eur Heart J.* 2022;43:4406-4417.

3. Tsujimoto T, Kaijo H. Abdominal Obesity Is Associated With an Increased Risk of All-Cause Mortality in Patients With HFpEF. *J Am Coll Cardiol.* 2017;70:2739-2749.

4. Savji N, Meijers WC, Bartz TM, et al. The Association of Obesity and Cardiometabolic Traits With Incident HFpEF and HFrEF. *JACC Heart Fail.* 2018;6:701-709.

5. McMurray JJV, Jackson AM, Lam CSP, et al. Effects of Sacubitril-Valsartan Versus Valsartan in Women Compared With Men With Heart Failure and Preserved Ejection Fraction: Insights From PARAGON-HF. *Circulation.* 2019;141:338-351.

6. Pandey A, Vaduganathan M, Arora S, et al. Temporal Trends in Prevalence & Prognostic Implications of Comorbidities among Patients with Acute Decompensated Heart Failure: the ARIC Study Community Surveillance. *Circulation.* 2020;142:230-243.

7. McDonagh TA, Metra M, Adamo M, et al. 2021 ESC Guidelines for the Diagnosis and Treatment of Acute and Chronic Heart Failure. *Eur Heart J.* 2021;42:3599-3726.

8. Heidenreich PA, Bozkurt B, Aguilar D, et al. 2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. *Circulation.* 2022;145:e895-e1032.

9. Wang TJ, Larson MG, Levy D, et al. Impact of Obesity on Plasma Natriuretic Peptide Levels. *Circulation.* 2004;109:594-600.

10. Dessì-Fulgheri P, Sarzani R, Rappelli A. Role of the Natriuretic Peptide System in Lipogenesis/Lipolysis. *Nutr Metab Cardiovasc Dis.* 2003;13:244-249.

11. Neeland IJ, Winders BR, Ayers CR, et al. Higher Natriuretic Peptide Levels Associate With a Favorable Adipose Tissue Distribution Profile. *J Am Coll Cardiol.* 2013;62:752-760.

12. Obokata M, Reddy YNV, Pislaru SV, et al. Evidence Supporting the Existence of a Distinct Obese Phenotype of Heart Failure With Preserved Ejection Fraction. *Circulation.* 2017;136:6-19.

13. Arora P, Wu C, Hamid T, et al. Acute Metabolic Influences on the Natriuretic Peptide System in Humans. *J Am Coll Cardiol.* 2016;67:804-812.

14. Jordan J, Birkenfeld AL, Melander O, Moro C. Natriuretic Peptides in Cardiovascular and Metabolic Crosstalk: Implications for Hypertension Management. *Hypertension.* 2018;72:270-276.

15. Parcha V, Patel N, Musunuru K, et al. Natriuretic Peptide Deficiency in Obese Individuals: Mechanistic Insights From Healthy Organ Donor Cohort. *J Am Coll Cardiol.* 2021;77:3138-3140.

16. Gommans DHF, Revuelta-Lopez E, Lupon J, et al. Soluble Neprilysin and Corin Concentrations in Relation to Clinical Outcome in Chronic Heart Failure. *JACC Heart Fail.* 2021;9:85-95.

17. Das SR, Drazner MH, Dries DL, et al. Impact of Body Mass and Body Composition on Circulating Levels of Natriuretic Peptides: Results From the Dallas Heart Study. *Circulation.* 2005;112:2163-2168.
18. Palmer SC, Yandle TG, Nicholls MG, et al. Regional Clearance of Amino-Terminal Pro-Brain Natriuretic Peptide from Human Plasma. *Eur J Heart Fail.* 2009;11:832-839.

19. Selvaraj S, Kim J, Ansari BA, et al. Body Composition, Natriuretic Peptides, and Adverse Outcomes in Heart Failure With Preserved and Reduced Ejection Fraction. *JACC Cardiovasc Imaging*. 2021;14:203-215.

20. Forbes GB, Welle SL. Lean Body Mass in Obesity. *Int J Obes*. 1983;7:99-107.

21. Raghupathy R, McLean RR, Kiel DP, et al. Higher Abdominal Adiposity is Associated with Higher Lean Muscle Mass but Lower Muscle Quality in Middle-Aged and Older Men and Women: The Framingham Heart Study. *Aging Clin Exp Res*. 2023;35:1477-1485.

22. NCD Risk Factor Collaboration (NCD-RisC): Phelps NH, Singleton RK, Zhou B, et al. Worldwide Trends in Underweight and Obesity from 1990 to 2022: A Pooled Analysis of 3663 Population-Representative Studies with 222 Million Children, Adolescents, and Adults. *Lancet*. 2024;403:1027-1050.

23. Bozkurt, Ahmad T, Alexander K, et al. HF STATS 2024: Heart Failure Epidemiology and Outcomes Statistics An Updated 2024 Report from the Heart Failure Society of America. *J Card Fail.* 2024;Epub ahead of print. DOI: 10.1016/j.cardfail.2024.07.001

24. Ward ZJ, Bleich SN, Cradock AL, et al. Projected U.S. State-Level Prevalence of Adult Obesity and Severe Obesity. *N Engl J Med.* 2019;381:2440-2450.

25. Mehra MR, Uber PA, Park MH, et al. Obesity and Suppressed B-Type Natriuretic Peptide Levels in Heart Failure. *J Am Coll Cardiol*. 2004;43:1590-1595.

26. Bayes-Genis A, Lloyd-Jones DM, van Kimmenade RR, et al. Effect of Body Mass Index on Diagnostic and Prognostic Usefulness of Amino-Terminal Pro-Brain Natriuretic Peptide in Patients With Acute Dyspnea. *Arch Intern Med.* 2007;167:400-407.

27. Myhre PL, Vaduganathan M, Claggett BL, et al. Association of Natriuretic Peptides With Cardiovascular Prognosis in Heart Failure With Preserved Ejection Fraction: Secondary Analysis of the TOPCAT Randomized Clinical Trial. *JAMA Cardiol*. 2018;3:1000-1005.

28. Cunningham JW, Vaduganathan M, Claggett BL, et al. Effects of Sacubitril/Valsartan on N-Terminal Pro-B-Type Natriuretic Peptide in Heart Failure With Preserved Ejection Fraction. *JACC Heart Fail.* 2020;8:372-381.

29. Massie BM, Carson PE, McMurray JJ, et al. Irbesartan in Patients with Heart Failure and Preserved Ejection Fraction. *N Engl J Med.* 2008;359:2456-2467.

30. Pitt B, Pfeffer MA, Assmann SF, et al. Spironolactone for Heart Failure with Preserved Ejection Fraction. *N Engl J Med.* 2014;370:1383-1392.

31. Solomon SD, McMurray JJV, Anand IS, et al. Angiotensin-Neprilysin Inhibition in Heart Failure with Preserved Ejection Fraction. *N Engl J Med.* 2019;381:1609-1620.

32. Solomon SD, McMurray JJV, Claggett B, et al. Dapagliflozin in Heart Failure with Mildly Reduced or Preserved Ejection Fraction. *N Engl J Med.* 2022;387:1089-1098.

33. Shah SJ, Heitner JF, Sweitzer NK, et al. Baseline Characteristics of Patients in the Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist (TOPCAT) Trial. *Circ Heart Fail.* 2012;6:184-192.

34. Solomon SD, Rizkala AR, Lefkowitz MP, et al. Baseline Characteristics of Patients With Heart Failure and Preserved Ejection Fraction in the PARAGON-HF Trial. *Circ Heart Fail.* 2018;11:e004962.
35. Solomon SD, Vaduganathan M, Claggett BL, et al. Baseline Characteristics of Patients With HF With Mildly Reduced and Preserved Ejection Fraction: DELIVER Trial. *JACC Heart Fail.* 2022;10:184-197.

36. Pfeffer MA, Claggett B, Assmann SF, et al. Regional Variation in Patients and Outcomes in the Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist (TOPCAT) Trial. *Circulation.* 2015;131:34-42.

37. de Danus S, O'Meara E, Desai AS, et al. Spironolactone Metabolites in TOPCAT — New Insights into Regional Variation. *N Engl J Med.* 2017;376:1690-1692.

38. Jhund PS, Anand IS, Komajda M, et al. Changes in N-terminal Pro-B-Type Natriuretic Peptide Levels and Outcomes in Heart Failure with Preserved Ejection Fraction: An Analysis of the I-Preserve Study. *Eur J Heart Fail.* 2015;17:809-817.

39. Myhre P, Vaduganathan M, Claggett BL, et al. Influence of NT-proBNP on Efficacy of Dapagliflozin in Heart Failure With Mildly Reduced or Preserved Ejection Fraction. *JACC Heart Fail.* 2022;10:902-913.

40. Anand IS, Claggett B, Liu J, et al. Interaction Between Spironolactone and Natriuretic Peptides in Patients With Heart Failure and Preserved Ejection Fraction: From the TOPCAT Trial. *JACC Heart Fail.* 2017;5:241-252.

41. Matsushita K, Coresh J, Sang Y, et al. Estimated Glomerular Filtration Rate and Albuminuria for Prediction of Cardiovascular Outcomes: A Collaborative Meta-Analysis of Individual Participant Data. *Lancet Diabetes Endocrinol.* 2015;3:514-525.

42. Lu H, Kondo T, Claggett BL, et al. Systolic Blood Pressure and Pulse Pressure in Heart Failure: Pooled Participant-Level Analysis of 4 Trials. *J Am Coll Cardiol.* 2025;85:710-722.

43. Neuen BL, Vaduganathan M, Claggett BL, et al. Natriuretic Peptides, Kidney Function, and Clinical Outcomes in Heart Failure With Preserved Ejection Fraction. *JACC Heart Fail.* 2025;13:28-39.

44. Reddy YNV, Tada A, Obokata M, et al. Evidence-Based Application of Natriuretic Peptides in the Evaluation of Chronic Heart Failure With Preserved Ejection Fraction in the Ambulatory Outpatient Setting. *Circulation.* 2025;151:976-989.

45. Vaishnav J, Chasler JE, Lee YJ, et al. Highest Obesity Category Associated With Largest Decrease in N- Terminal Pro- B- Type Natriuretic Peptide in Patients Hospitalized With Heart Failure With Preserved Ejection Fraction. *J Am Heart Assoc.* 2020;9:e015738.

46. GBD 2021 Risk Factors Collaborators: Brauer M, Roth GA, Aravkin AY, et al. Global Burden and Strength of Evidence for 88 Risk Factors in 204 Countries and 811 Subnational Locations, 1990-2021: A Systematic Analysis for the Global Burden of Disease Study 2021. *Lancet.* 2024;403:2162-2203.

47. Khan SS, Breathett K, Braun LT, et al. Risk-Based Primary Prevention of Heart Failure: A Scientific Statement From the American Heart Association. *Circulation.* 2025;151:e1006-e1026.

48. American Diabetes Association Professional Practice Committee: ElSayed NA, Aleppo G, Bannuru RR, et al. 10. Cardiovascular Disease and Risk Management: Standards of Care in Diabetes-2024. *Diabetes Care.* 2024;47(Suppl 1):S179-S218.

49. Packer M, Zile MR, Kramer CM, et al. Tirzepatide for Heart Failure with Preserved Ejection Fraction and Obesity. *N Engl J Med.* 2025;392:427-437.
<table><caption>Table 1: Baseline Characteristics of the Pooled Trial Participants, by Baseline Body Mass Index</caption><thead><tr><th rowspan="2">Characteristic</th><th rowspan="2">Overall<br>(n=14750)</th><th colspan="5">Baseline BMI Category (kg/m²)</th></tr><tr><th>18.5 to &lt;25<br>(n=2711)</th><th>25 to &lt;30<br>(n=5298)</th><th>30 to &lt;35<br>(n=3984)</th><th>35 to &lt;40<br>(n=2141)</th><th>≥40<br>(n=616)</th></tr></thead><tbody><tr><td>Age, y</td><td>72 ± 9</td><td>74 ± 9</td><td>73 ± 9</td><td>72 ± 8</td><td>70 ± 8</td><td>68 ± 8</td></tr><tr><td>Female</td><td>7415 (50.3%)</td><td>1311 (48.4%)</td><td>2496 (47.1%)</td><td>2021 (50.7%)</td><td>1193 (55.7%)</td><td>394 (64.0%)</td></tr><tr><td>Race</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Asian</td><td>1884 (12.8%)</td><td>884 (32.6%)</td><td>741 (14.0%)</td><td>207 (5.2%)</td><td>44 (2.1%)</td><td>8 (1.3%)</td></tr><tr><td>Black</td><td>364 (2.5%)</td><td>44 (1.6%)</td><td>109 (2.1%)</td><td>88 (2.2%)</td><td>74 (3.5%)</td><td>49 (8.0%)</td></tr><tr><td>White</td><td>11797 (80.0%)</td><td>1629 (60.1%)</td><td>4195 (79.2%)</td><td>3493 (87.7%)</td><td>1948 (91.0%)</td><td>532 (86.4%)</td></tr><tr><td>Other</td><td>705 (4.8%)</td><td>154 (5.7%)</td><td>253 (4.8%)</td><td>196 (4.9%)</td><td>75 (3.5%)</td><td>27 (4.4%)</td></tr><tr><td>Trial</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>I-Preserve</td><td>3541 (23.4%)</td><td>570 (21.0%)</td><td>1461 (27.6%)</td><td>928 (23.3%)</td><td>357 (16.7%)</td><td>135 (21.9%)</td></tr><tr><td>TOPCAT-Americas</td><td>355 (2.4%)</td><td>60 (2.2%)</td><td>95 (1.8%)</td><td>90 (2.3%)</td><td>66 (3.1%)</td><td>44 (7.1%)</td></tr><tr><td>PARAGON-HF</td><td>4742 (32.1%)</td><td>738 (27.2%)</td><td>1669 (31.5%)</td><td>1392 (34.9%)</td><td>920 (43.0%)</td><td>23 (3.7%)</td></tr><tr><td>DELIVER</td><td>6202 (42.0%)</td><td>1343 (49.5%)</td><td>2073 (39.1%)</td><td>1574 (39.5%)</td><td>798 (37.3%)</td><td>414 (67.2%)</td></tr><tr><td>BMI, kg/m²</td><td>30.0 ± 5.6</td><td>22.9 ± 1.6</td><td>27.5 ± 1.4</td><td>32.2 ± 1.4</td><td>37.2 ± 1.5</td><td>43.7 ± 3.5</td></tr><tr><td>Waist circumference, cm<sup>a</sup></td><td>104.8 ± 15.0</td><td>88.6 ± 9.5</td><td>99.5 ± 10.0</td><td>109.3 ± 12.0</td><td>118.9 ± 12.0</td><td>129.2 ± 17.7</td></tr><tr><td>Elevated waist circumference<sup>b</sup></td><td>3736 (77.2%)</td><td>272 (35.9%)</td><td>1178 (70.4%)</td><td>1290 (92.4%)</td><td>931 (98.4%)</td><td>65 (98.5%)</td></tr><tr><td>Waist-to-height ratio<sup>a</sup></td><td>0.63 ± 0.09</td><td>0.54 ± 0.05</td><td>0.60 ± 0.06</td><td>0.66 ± 0.07</td><td>0.72 ± 0.07</td><td>0.78 ± 0.11</td></tr><tr><td>Waist-to-height ratio ≥0.5<sup>a</sup></td><td>4628 (95.6%)</td><td>604 (79.8%)</td><td>1627 (97.2%)</td><td>1387 (99.4%)</td><td>944 (99.8%)</td><td>66 (100.0%)</td></tr><tr><td>Systolic blood pressure, mm Hg</td><td>131 ± 16</td><td>128 ± 16</td><td>131 ± 15</td><td>132 ± 15</td><td>132 ± 16</td><td>132 ± 17</td></tr><tr><td>Diastolic blood pressure, mm Hg</td><td>75 ± 10</td><td>73 ± 10</td><td>75 ± 10</td><td>76 ± 10</td><td>76 ± 10</td><td>76 ± 12</td></tr><tr><td>Heart rate, bpm</td><td>71 ± 12</td><td>71 ± 12</td><td>71 ± 12</td><td>71 ± 11</td><td>71 ± 12</td><td>72 ± 12</td></tr><tr><td>NYHA functional class</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>I</td><td>146 (1.0%)</td><td>30 (1.1%)</td><td>57 (1.1%)</td><td>42 (1.1%)</td><td>16 (0.7%)</td><td>1 (0.2%)</td></tr><tr><td>II</td><td>9263 (62.8%)</td><td>1821 (67.2%)</td><td>3347 (63.2%)</td><td>2461 (61.8%)</td><td>1336 (62.4%)</td><td>298 (48.4%)</td></tr><tr><td>III</td><td>5210 (35.3%)</td><td>835 (30.8%)</td><td>1846 (34.9%)</td><td>1455 (36.5%)</td><td>764 (35.7%)</td><td>310 (50.3%)</td></tr><tr><td>IV</td><td>128 (0.9%)</td><td>25 (0.9%)</td><td>47 (0.9%)</td><td>25 (0.6%)</td><td>24 (1.1%)</td><td>7 (1.1%)</td></tr><tr><td>LVEF, %</td><td>57 ± 9</td><td>56 ± 9</td><td>57 ± 9</td><td>57 ± 9</td><td>57 ± 9</td><td>57 ± 9</td></tr><tr><td>eGFR, mL/min/1.73 m²</td><td>64.3 ± 20.5</td><td>64.6 ± 20.5</td><td>65.2 ± 20.5</td><td>63.7 ± 20.1</td><td>62.5 ± 20.3</td><td>64.7 ± 22.7</td></tr><tr><td>eGFR &lt;60 mL/min/1.73 m²</td><td>6584 (44.6%)</td><td>1185 (43.7%)</td><td>2259 (42.6%)</td><td>1827 (45.9%)</td><td>1028 (48.0%)</td><td>285 (46.3%)</td></tr><tr><td>NT-proBNP, pg/mL</td><td>836 [423, 1557]</td><td>1028 [522, 1956]</td><td>840 [419, 1597]</td><td>773 [395, 1478]</td><td>759 [401, 1327]</td><td>761 [413, 1278]</td></tr></tbody></table>
<table><tbody><tr><td>History of hypertension</td><td>13413 (90.9%)</td><td>2258 (83.3%)</td><td>4760 (89.8%)</td><td>3755 (94.3%)</td><td>2055 (96.0%)</td><td>585 (95.0%)</td></tr><tr><td>History of diabetes</td><td>5939 (40.3%)</td><td>759 (28.0%)</td><td>1930 (36.4%)</td><td>1784 (44.8%)</td><td>1123 (52.5%)</td><td>343 (55.7%)</td></tr><tr><td>History of atrial fibrillation</td><td>7087 (48.0%)</td><td>1299 (47.9%)</td><td>2383 (45.0%)</td><td>1970 (49.4%)</td><td>1131 (52.8%)</td><td>304 (49.4%)</td></tr><tr><td>History of stroke</td><td>1464 (9.9%)</td><td>286 (10.6%)</td><td>551 (10.4%)</td><td>382 (9.6%)</td><td>209 (9.8%)</td><td>36 (5.8%)</td></tr><tr><td>History of myocardial infarction</td><td>3611 (24.5%)</td><td>686 (25.3%)</td><td>1436 (27.1%)</td><td>928 (23.3%)</td><td>455 (21.3%)</td><td>106 (17.2%)</td></tr><tr><td>ACEI/ARB</td><td>11028 (74.8%)</td><td>1842 (68.0%)</td><td>3927 (74.1%)</td><td>3085 (77.4%)</td><td>1704 (79.6%)</td><td>470 (76.3%)</td></tr><tr><td>β-blocker</td><td>11239 (76.2%)</td><td>1927 (71.2%)</td><td>3938 (74.3%)</td><td>3132 (78.6%)</td><td>1757 (82.1%)</td><td>485 (78.7%)</td></tr><tr><td>Spirolactone</td><td>4567 (31.0%)</td><td>952 (35.1%)</td><td>1533 (28.9%)</td><td>1224 (30.7%)</td><td>631 (29.5%)</td><td>227 (36.9%)</td></tr><tr><td>Any diuretic</td><td>13754 (93.3%)</td><td>2484 (91.8%)</td><td>4855 (91.7%)</td><td>3747 (94.1%)</td><td>2063 (96.4%)</td><td>605 (98.2%)</td></tr></tbody></table>

Characteristics presented as n (%), mean ± SD, or median [IQR], and compared through analysis of variance, Kruskal-Wallis, or $\chi^2$ testing.

<sup>a</sup>: Waist circumference, and therefore, waist-to-height ratio, was collected only in TOPCAT and PARAGON-HF.

<sup>b</sup>: Elevated waist circumference defined as: waist circumference >88/102 cm for female and male participants with self-reported race other than Asian, respectively, or waist circumference ≥80/90 for female and male participants with self-reported Asian race, respectively.

Abbreviations: ACEI = angiotensin-converting enzyme inhibitor; ARB = angiotensin receptor blocker; BMI = body mass index; DELIVER = Dapagliflozin Evaluation to Improve the Lives of Patients With Preserved Ejection Fraction Heart Failure; eGFR = estimated glomerular filtration rate; I-Preserve = Irbesartan in Heart Failure and Preserved Ejection Fraction; LVEF = left ventricular ejection fraction; NT-proBNP = N-terminal pro-B-type natriuretic peptide; NYHA = New York Heart Association; PARAGON-HF = Prospective Comparison of Angiotensin Receptor-Nephrilysin Inhibitor with Angiotensin Receptor Blocker Global Outcomes in HF with Preserved Ejection Fraction; TOPCAT = Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist
<table><caption>Table 2: Clinical Outcomes per Doubling of Baseline NT-proBNP, by BMI Category</caption><thead><tr><th>Outcome and BMI Category</th><th>aHR (95% CI) per Doubling of Baseline NT-proBNP</th><th>P<sub>interaction</sub></th></tr></thead><tbody><tr><td colspan="3"><strong>CV Death or HF Hospitalization (Overall aHR = 1.40 [1.36 to 1.43]; P&lt;0.001)</strong></td></tr><tr><td>≥18.5 to &lt;25 kg/m<sup>2</sup></td><td>1.48 (1.39 to 1.57); P&lt;0.001</td><td rowspan="5">0.008</td></tr><tr><td>≥25 to &lt;30 kg/m<sup>2</sup></td><td>1.43 (1.36 to 1.50); P&lt;0.001</td></tr><tr><td>≥30 to &lt;35 kg/m<sup>2</sup></td><td>1.35 (1.28 to 1.43); P&lt;0.001</td></tr><tr><td>≥35 to &lt;40 kg/m<sup>2</sup></td><td>1.31 (1.21 to 1.42); P&lt;0.001</td></tr><tr><td>≥40 kg/m<sup>2</sup></td><td>1.32 (1.14 to 1.53); P&lt;0.001</td></tr><tr><td colspan="3"><strong>HF Hospitalization (Overall aHR = 1.39 [1.34 to 1.43]; P&lt;0.001)</strong></td></tr><tr><td>≥18.5 to &lt;25 kg/m<sup>2</sup></td><td>1.48 (1.37 to 1.60); P&lt;0.001</td><td rowspan="5">0.004</td></tr><tr><td>≥25 to &lt;30 kg/m<sup>2</sup></td><td>1.42 (1.34 to 1.51); P&lt;0.001</td></tr><tr><td>≥30 to &lt;35 kg/m<sup>2</sup></td><td>1.36 (1.28 to 1.45); P&lt;0.001</td></tr><tr><td>≥35 to &lt;40 kg/m<sup>2</sup></td><td>1.27 (1.16 to 1.38); P&lt;0.001</td></tr><tr><td>≥40 kg/m<sup>2</sup></td><td>1.33 (1.12 to 1.57); P=0.001</td></tr><tr><td colspan="3"><strong>CV Death (Overall aHR = 1.47 [1.41 to 1.53]; P&lt;0.001)</strong></td></tr><tr><td>≥18.5 to &lt;25 kg/m<sup>2</sup></td><td>1.55 (1.43 to 1.68); P&lt;0.001</td><td rowspan="5">0.17</td></tr><tr><td>≥25 to &lt;30 kg/m<sup>2</sup></td><td>1.48 (1.39 to 1.58); P&lt;0.001</td></tr><tr><td>≥30 to &lt;35 kg/m<sup>2</sup></td><td>1.42 (1.32 to 1.54); P&lt;0.001</td></tr><tr><td>≥35 to &lt;40 kg/m<sup>2</sup></td><td>1.48 (1.30 to 1.68); P&lt;0.001</td></tr><tr><td>≥40 kg/m<sup>2</sup></td><td>1.36 (1.09 to 1.70); P=0.006</td></tr><tr><td colspan="3"><strong>All-Cause Death (Overall aHR = 1.39 [1.34 to 1.43]; P&lt;0.001)</strong></td></tr><tr><td>≥18.5 to &lt;25 kg/m<sup>2</sup></td><td>1.39 (1.34 to 1.43); P&lt;0.001</td><td rowspan="5">0.09</td></tr><tr><td>≥25 to &lt;30 kg/m<sup>2</sup></td><td>1.48 (1.39 to 1.58); P&lt;0.001</td></tr><tr><td>≥30 to &lt;35 kg/m<sup>2</sup></td><td>1.39 (1.32 to 1.46); P&lt;0.001</td></tr><tr><td>≥35 to &lt;40 kg/m<sup>2</sup></td><td>1.36 (1.28 to 1.44); P&lt;0.001</td></tr><tr><td>≥40 kg/m<sup>2</sup></td><td>1.32 (1.20 to 1.46); P&lt;0.001</td></tr></tbody></table>

aHR estimated through Cox proportional hazards regression models adjusted for age, sex, race, history of atrial fibrillation, baseline body mass index (incorporated as a spline term), estimated glomerular filtration rate (incorporated as a spline term), systolic blood pressure (incorporated as a spline term), baseline diuretic use, trial, and randomized treatment.

Abbreviations: aHR = adjusted hazard ratio; BMI = body mass index; CV = cardiovascular; HF = heart failure; NT-proBNP = N-terminal prohormone of B-type natriuretic peptide
<table><caption>Table 3: NT-proBNP Concentrations Corresponding to Specific Rates of Clinical Outcomes Overall in Participants without Atrial Fibrillation, Stratified by Baseline Body Mass Index Category</caption><thead><tr><th rowspan="2">Outcome and Event Rate</th><th colspan="5">Estimated NT-proBNP Concentrations (pg/mL) at Specific Event Rates, by BMI Category (kg/m²)</th></tr><tr><th>18.5 to &lt;25</th><th>25 to &lt;30</th><th>30 to &lt;35</th><th>35 to &lt;40</th><th>≥40</th></tr></thead><tbody><tr><td><strong>CV Death or HF Hospitalization</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>5 per 100 person-years</td><td>484 (380, 617)</td><td>502 (428, 589)</td><td>372 (299, 462)</td><td>158 (96, 259)</td><td>155 (67, 358)</td></tr><tr><td>10 per 100 person-years</td><td>1413 (1171, 1705)</td><td>1500 (1287, 1750)</td><td>1285 (1053, 1570)</td><td>773 (564, 1060)</td><td>665 (402, 1100)</td></tr><tr><td><strong>HF Hospitalization</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>5 per 100 person-years</td><td>973 (772, 1226)</td><td>1225 (1029, 1459)</td><td>722 (586, 889)</td><td>293 (193, 445)</td><td>356 (191, 664)</td></tr><tr><td>10 per 100 person-years</td><td>2733 (2087, 3582)</td><td>3332 (2590, 4283)</td><td>2303 (1758, 3012)</td><td>1450 (894, 2353)</td><td>1329 (668, 2645)</td></tr><tr><td><strong>CV Death</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>5 per 100 person-years</td><td>1220 (964, 1563)</td><td>1358 (1125, 1639)</td><td>1579 (1181, 2112)</td><td>1373 (839, 2247)</td><td>963 (393, 2359)</td></tr><tr><td>10 per 100 person-years</td><td>3456 (2554, 4677)</td><td>3961 (2982, 5255)</td><td>5319 (3334, 8491)</td><td>4944 (1998, 12150)</td><td>4681 (724, 29988)</td></tr><tr><td><strong>All-Cause Death</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>5 per 100 person-years</td><td>540 (416, 701)</td><td>606 (509, 722)</td><td>641 (520, 791)</td><td>576 (413, 803)</td><td>331 (176, 622)</td></tr><tr><td>10 per 100 person-years</td><td>1797 (1431, 2258)</td><td>2103 (1709, 2590)</td><td>2223 (1709, 2884)</td><td>2329 (1318, 4121)</td><td>1319 (633, 2623)</td></tr></tbody></table>

Event rates estimated through Poisson regression. Uncertainty intervals reflect values of NT-proBNP at the lower and upper bounds of the 95% CI of the specified incidence rate.

Abbreviations: BMI = body mass index; CV = cardiovascular; HF = heart failure; NT-proBNP = N-terminal pro-B-type natriuretic peptide
Central Illustration: NT-proBNP, BMI, and Clinical Outcomes in HFmrEF/HFpEF

Design

Participant-level
pooled analysis of
4 global HFpEF
clinical trials

I-Preserve
TOPCAT-Americas
PARAGON-HF
DELIVER

n=14,750 with BMI and NT-proBNP

<figure><img src="image_2.png" /></figure>

NT-proBNP and BMI at Baseline

<figure><img src="image_3.png" /></figure>

NT-proBNP significantly & non-linearly associated with BMI

CVD or HFH, per NT-proBNP Doubling

<figure><img src="image_4.png" /></figure>

↑ baseline NT-proBNP associated with ↑ CVD or HFH in
all BMI categories, but association blunted with ↑ BMI

NT-proBNP and Absolute Risk*, by BMI

<figure><img src="image_5.png" /></figure>

At specific NT-proBNP levels, risk of CVD or HFH ↑ with
↑ BMI; at specific risk levels, NT-proBNP ↓ with ↑ BMI

Current NT-proBNP thresholds appear to substantially underestimate absolute risks of adverse HF outcomes among persons with HFpEF and elevated BMI. These data suggest that lower NT-proBNP cutoffs may more appropriately risk stratify persons with higher BMI.

Graphic details the key design features and findings of a participant-level pooled analysis of 4 trials examining the interplay between BMI, NT-proBNP, and clinical outcomes. IR (per 100 py) in bottom right panel refer to cardiovascular death or heart failure hospitalization.

Abbreviations: BMI = body mass index; CVD = cardiovascular death; HF = heart failure; HFH = heart failure hospitalization; HFpEF = heart failure with preserved ejection fraction; IR = incidence rate; NT-proBNP = N-terminal prohormone of B-type natriuretic peptide; py = person-years

<footnote>*: CVD or HFH</footnote>
<figure><img src="image_6.png" /><figcaption>Figure 1: Distribution of Baseline NT-proBNP, by Baseline BMI Category</figcaption></figure>

Figure shows the smoothed distribution of baseline NT-proBNP according to baseline BMI category.

Abbreviations: BMI = body mass index; IQR = interquartile range; NT-proBNP = N-terminal pro-B-type natriuretic peptide
<figure><img src="image_7.png" /><figcaption>Figure 2: Continuous Flexible Association Between BMI and NT-proBNP at Baseline</figcaption></figure>

Figure shows the distribution of body mass index at baseline (histogram), as well as a restricted cubic spline (3 knots) demonstrating the continuous flexible association between baseline body mass index and mean (95% CI) NT-proBNP values, estimated through linear regression with adjustment for age, sex, race, history of atrial fibrillation, estimated glomerular filtration rate (incorporated as a spline term), systolic blood pressure (incorporated as a spline term), baseline diuretic use, trial, and randomized treatment.

Abbreviations: BMI = body mass index; NT-proBNP = N-terminal pro-B-type natriuretic peptide
<figure><img src="image_8.png" /><figcaption>Figure 3: NT-proBNP and Clinical Outcomes, by Baseline BMI Category</figcaption></figure>

Figures show the association between doubling of NT-proBNP values with CV death or HF hospitalization (A), HF hospitalization (B), CV death (C), and all-cause death (D) according to baseline BMI category. Adjusted hazard ratios (with 95% CI) estimated through Cox proportional hazards regression models, using BMI 18.5 to <25 kg/m² and NT-proBNP = 500 pg/mL as reference, presented using linear models with adjustment for age, sex, race, history of atrial fibrillation, estimated glomerular filtration rate (incorporated as a spline term), systolic blood pressure (incorporated as a spline term), baseline diuretic use, trial, and randomized treatment.

Abbreviations: BMI = body mass index; CV = cardiovascular; HF = heart failure; NT-proBNP = N-terminal pro-B-type natriuretic peptide
<figure><img src="image_9.png" /><figcaption>Figure 4: Continuous Flexible Associations Between BMI, NT-proBNP, and Incidence of Clinical Outcomes</figcaption></figure>

Contour plots show the predicted incidence rates (per 100 person-years) for CV death or HF hospitalization (A), HF hospitalization (B), CV death (C), and all-cause death (D) at any given level of BMI or NT-proBNP. Predicted incidence rates estimated through Poisson regression, using the overall mean pooled trial population age of 72 years, and adjusted for sex and history of atrial fibrillation.
Scatterplot showing individual-level data additionally provided for reference.

Abbreviations: BMI = body mass index; CV = cardiovascular; HF = heart failure; NT-proBNP = N-terminal pro-B-type natriuretic peptide
<caption>**Figure 5:** Predicted Incidence Rates of CV Death or HF Hospitalization at Recent Trial NT-proBNP Eligibility Thresholds, by Baseline BMI Category</caption>

<figure><img src="image_10.png" /><figcaption>**B:** Predicted IR at NT-proBNP = 600 pg/mL, Among Participants with AF</figcaption></figure>

<figure><img src="image_11.png" /></figure>

Figures show predicted incidence rates (per 100 py) of CV death or HF hospitalization according to NT-proBNP eligibility thresholds recently employed in HFmrEF/HFpEF clinical trials for individuals without (A) and with a history of AF (B), by baseline BMI category. Incidence rates (and 95% CI) estimated through Poisson regression, adjusted for age, sex, and eGFR.

Abbreviations: BMI = body mass index; CV = cardiovascular; eGFR = estimated glomerular filtration rate; HF = heart failure; IR = incidence rate; NT-proBNP = N-terminal pro-B-type natriuretic peptide; py = person-years
# Natriuretic Peptides, Body Mass Index, and Clinical Outcomes in Heart Failure with Mildly Reduced or Preserved Ejection Fraction

## Supplementary Data

## Table of Contents

### - Tables

* Supplementary Table 1: BMI- and NT-proBNP-Based Eligibility Criteria in I-Preserve, TOPCAT, PARAGON-HF, and DELIVER

* Supplementary Table 2: Clinical Outcomes Per Doubling of NT-proBNP, Original and Landmarked Models

* Supplementary Table 3: Clinical Outcomes Per Doubling of Baseline NT-proBNP, Excluding TOPCAT-Americas

* Supplementary Table 4: Clinical Outcomes Per Doubling of Baseline NT-proBNP, Adjustment for Blood Pressure and eGFR as Linear Terms

* Supplementary Table 5: Clinical Outcomes Per Doubling of Baseline NT-proBNP, Considering Competing Risk of Death

* Supplementary Table 6: Selected Cardiovascular Outcomes Per Doubling of Baseline NT-proBNP, by Alternative BMI Category

* Supplementary Table 7: NT-proBNP Concentrations Corresponding to Specific Rates of Clinical Outcomes Overall in Participants without Atrial Fibrillation, Stratified by Alternative Baseline Body Mass Index Categories

### - Figures

* Supplementary Figure 1: Scatterplot of Baseline BMI and Log-Transformed NT-proBNP

* Supplementary Figure 2: Continuous Flexible Association Between BMI and NT-proBNP at Baseline, According to Age, Sex, and Race

* Supplementary Figure 3: Continuous Flexible Association Between BMI and NT-proBNP at Baseline, According to History of Atrial Fibrillation

* Supplementary Figure 4: NT-proBNP and Clinical Outcomes, by Baseline BMI Category, Excluding TOPCAT-Americas

* Supplementary Figure 5: NT-proBNP and Clinical Outcomes According to Alternative BMI Subgroups

* Supplementary Figure 6: Continuous Flexible Associations Between BMI, NT-proBNP, and Incidence of Selected Clinical Outcomes According to History of Atrial Fibrillation

* Supplementary Figure 7: Predicted Incidence Rates of HF Hospitalization at Recent Trial NT-proBNP Eligibility Thresholds, by Baseline BMI Category

* Supplementary Figure 8: Predicted Incidence Rates of CV Death at Recent Trial NT-proBNP Eligibility Thresholds, by Baseline BMI Category

* Supplementary Figure 9: Predicted Incidence Rates of Outcomes at Recent Trial NT-proBNP Eligibility Thresholds, Alternative BMI Categories

* Supplementary Figure 10: Predicted Incidence Rates of CV Death or HF Hospitalization at Recent Trial NT-proBNP Eligibility Thresholds by Baseline BMI Category, Restricting to I-Preserve and TOPCAT-Americas Alone

* Supplementary Figure 11: Predicted Incidence Rates of Clinical Outcomes at Recently Proposed BMI-Based Rule-In NT-proBNP Thresholds
<table><caption>Supplementary Table 1: BMI- and NT-proBNP-Based Eligibility Criteria in I-Preserve, TOPCAT, PARAGON-HF, and DELIVER</caption><thead><tr><td>Trial</td><td>Enrollment Period</td><td>BMI-Based Eligibility Criteria</td><td>Key NT-proBNP-Based Eligibility Criteria</td></tr></thead><tbody><tr><td>I-Preserve</td><td>2002-2005</td><td>None</td><td>None</td></tr><tr><td>TOPCAT</td><td>2006-2012</td><td>None</td><td>At least one hospital admission in the last 12 months for which management of heart failure was a major component of the care provided<br>OR<br>Elevated natriuretic peptide levels (BNP ≥100 pg/mL or NT-proBNP ≥360 pg/mL) within 60 days of randomization</td></tr><tr><td>PARAGON-HF</td><td>2014-2016</td><td>BMI >40 kg/m² was exclusionary</td><td>HF hospitalization (defined as HF listed as the major reason for hospitalization) within 9 months prior to screening visit and NT-proBNP >200 pg/mL for patients not in AF or >600 pg/mL for patients in AF on screening ECG<br>OR<br>NT-proBNP >300 pg/mL for patients not in AF or >900 pg/mL for patients in AF on the screening visit ECG.</td></tr><tr><td>DELIVER</td><td>2018-2020</td><td>BMI >50 kg/m² was exclusionary</td><td>NT-proBNP ≥300 pg/mL at Visit 1 for patients without ongoing AFF<br>OR<br>NT-proBNP ≥600 pg/mL if ongoing AFF at Visit 1</td></tr></tbody></table>

Abbreviations: AF = atrial fibrillation; AFF = atrial fibrillation/ flutter; BMI = body mass index; BNP = B-type natriuretic peptide; NT-proBNP = N-terminal pro-B-type natriuretic peptide
<table><caption>Supplementary Table 2: Clinical Outcomes Per Doubling of NT-proBNP, Original and Landmarked Models</caption><thead><tr><th>Outcome</th><th>aHR (95% CI) per Doubling of Baseline NT-proBNP</th></tr></thead><tbody><tr><td colspan="2"><strong>Original (Non-Landmarked) Model<sup>a</sup></strong></td></tr><tr><td>CV death or HF hospitalization</td><td>1.40 (1.36 to 1.43); P&lt;0.001</td></tr><tr><td>CV death</td><td>1.47 (1.41 to 1.53); P&lt;0.001</td></tr><tr><td>HF hospitalization</td><td>1.39 (1.34 to 1.43); P&lt;0.001</td></tr><tr><td colspan="2"><strong>Model Landmarked at 21 Weeks<sup>b</sup></strong></td></tr><tr><td>CV death or HF hospitalization</td><td>1.35 (1.31 to 1.40); P&lt;0.001</td></tr><tr><td>CV death</td><td>1.44 (1.38 to 1.50); P&lt;0.001</td></tr><tr><td>HF hospitalization</td><td>1.34 (1.28 to 1.39); P&lt;0.001</td></tr></tbody></table>

Findings of Cox proportional hazards regression models adjusted for age, sex, race, history of atrial fibrillation, baseline body mass index (incorporated as a spline term), estimated glomerular filtration rate (incorporated as a spline term in the main model and as a linear term in the sensitivity model), systolic blood pressure (incorporated as a spline term in the main model and as a linear term in the sensitivity model), baseline diuretic use, trial, and randomized treatment.

Abbreviations: aHR = adjusted hazard ratio; CV = cardiovascular; HF = heart failure; NT-proBNP = N-terminal prohormone of B-type natriuretic peptide

<footnote><sup>a</sup>: Global test for proportional hazards violation (Schoenfeld residuals) for CV death or HF hospitalization: *P*<0.001</footnote>

<footnote><sup>b</sup>: Global test for proportional hazards violation (Schoenfeld residuals) for CV death or HF hospitalization: *P*=0.08</footnote>
<table><caption>Supplementary Table 3: Clinical Outcomes Per Doubling of Baseline NT-proBNP, Excluding TOPCAT-Americas</caption><thead><tr><th>Outcome</th><th>aHR (95% CI) per Doubling of Baseline NT-proBNP</th><th>P value for Interaction by Baseline BMI Category</th></tr></thead><tbody><tr><td colspan="3"><strong>Original Model; n=14,750</strong></td></tr><tr><td>CV death or HF hospitalization</td><td>1.40 (1.36 to 1.43); P&lt;0.001</td><td>0.008</td></tr><tr><td>CV death</td><td>1.47 (1.41 to 1.53); P&lt;0.001</td><td>0.17</td></tr><tr><td>HF hospitalization</td><td>1.39 (1.34 to 1.43); P&lt;0.001</td><td>0.004</td></tr><tr><td colspan="3"><strong>Sensitivity Model (Without TOPCAT-Americas); n=14,395</strong></td></tr><tr><td>CV death or HF hospitalization</td><td>1.39 (1.35 to 1.43); P&lt;0.001</td><td>0.012</td></tr><tr><td>CV death</td><td>1.47 (1.41 to 1.52); P&lt;0.001</td><td>0.33</td></tr><tr><td>HF hospitalization</td><td>1.38 (1.33 to 1.43); P&lt;0.001</td><td>0.007</td></tr></tbody></table>

Findings of Cox proportional hazards regression models adjusted for age, sex, race, history of atrial fibrillation, baseline body mass index (incorporated as a spline term), estimated glomerular filtration rate (incorporated as a spline term in the main model and as a linear term in the sensitivity model), systolic blood pressure (incorporated as a spline term in the main model and as a linear term in the sensitivity model), baseline diuretic use, trial, and randomized treatment.

Abbreviations: aHR = adjusted hazard ratio; CV = cardiovascular; HF = heart failure; NT-proBNP = N-terminal prohormone of B-type natriuretic peptide
<table><caption>Supplementary Table 4: Clinical Outcomes Per Doubling of Baseline NT-proBNP, Adjustment for Blood Pressure and eGFR as Linear Terms</caption><thead><tr><th>Outcome</th><th>aHR (95% CI) per Doubling of Baseline NT-proBNP</th><th>P value for Interaction by Baseline BMI Category</th></tr></thead><tbody><tr><td colspan="3"><strong>Original Model (Including SBP and eGFR as Spline Terms)</strong></td></tr><tr><td>CV death or HF hospitalization</td><td>1.40 (1.36 to 1.43); P&lt;0.001</td><td>0.008</td></tr><tr><td>CV death</td><td>1.47 (1.41 to 1.53); P&lt;0.001</td><td>0.17</td></tr><tr><td>HF hospitalization</td><td>1.39 (1.34 to 1.43); P&lt;0.001</td><td>0.004</td></tr><tr><td colspan="3"><strong>Sensitivity Model (Including SBP and eGFR as Linear Terms)</strong></td></tr><tr><td>CV death or HF hospitalization</td><td>1.40 (1.37 to 1.44); P&lt;0.001</td><td>0.007</td></tr><tr><td>CV death</td><td>1.48 (1.42 to 1.53); P&lt;0.001</td><td>0.14</td></tr><tr><td>HF hospitalization</td><td>1.39 (1.35 to 1.44); P&lt;0.001</td><td>0.004</td></tr></tbody></table>

Findings of Cox proportional hazards regression models adjusted for age, sex, race, history of atrial fibrillation, baseline body mass index (incorporated as a spline term), estimated glomerular filtration rate (incorporated as a spline term in the main model and as a linear term in the sensitivity model), systolic blood pressure (incorporated as a spline term in the main model and as a linear term in the sensitivity model), baseline diuretic use, trial, and randomized treatment.

Abbreviations: aHR = adjusted hazard ratio; CV = cardiovascular; eGFR = estimated glomerular filtration rate; HF = heart failure; NT-proBNP = N-terminal prohormone of B-type natriuretic peptide; SBP = systolic blood pressure
<table><caption>Supplementary Table 5: Clinical Outcomes Per Doubling of Baseline NT-proBNP, Considering Competing Risk of Death</caption><thead><tr><th>Outcome</th><th>aHR (95% CI) per Doubling of Baseline NT-proBNP</th><th>P value for Interaction by Baseline BMI Category</th></tr></thead><tbody><tr><td colspan="3"><strong>Original Model</strong></td></tr><tr><td>CV death or HF hospitalization</td><td>1.40 (1.36 to 1.43); P&lt;0.001</td><td>0.008</td></tr><tr><td>CV death</td><td>1.47 (1.41 to 1.53); P&lt;0.001</td><td>0.17</td></tr><tr><td>HF hospitalization</td><td>1.39 (1.34 to 1.43); P&lt;0.001</td><td>0.004</td></tr><tr><td>Outcome</td><td>Subdistribution HR (95% CI) per Doubling of Baseline NT-proBNP</td><td>P value for Interaction by Baseline BMI Category</td></tr><tr><td colspan="3"><strong>Sensitivity Models (Considering Competing Risks of Death)</strong></td></tr><tr><td>CV death or HF hospitalization<sup>a</sup></td><td>1.38 (1.34 to 1.42); P&lt;0.001</td><td>0.023</td></tr><tr><td>CV death<sup>a</sup></td><td>1.45 (1.39 to 1.51); P&lt;0.001</td><td>0.28</td></tr><tr><td>HF hospitalization<sup>b</sup></td><td>1.35 (1.30 to 1.39); P&lt;0.001</td><td>0.015</td></tr></tbody></table>

Competing risks of death considered through Fine-Gray subdistribution hazard models. All models adjusted for age, sex, race, history of atrial fibrillation, baseline body mass index (incorporated as a spline term), estimated glomerular filtration rate (incorporated as a spline term), systolic blood pressure (incorporated as a spline term), baseline diuretic use, trial, and randomized treatment.

Abbreviations: aHR = adjusted hazard ratio; CV = cardiovascular; HF = heart failure; HR = hazard ratio; NT-proBNP = N-terminal prohormone of B-type natriuretic peptide

<footnote><sup>a</sup>: Competing risk is non-cardiovascular death.</footnote>

<footnote><sup>b</sup>: Competing risk is all-cause death.</footnote>
<table><caption>Supplementary Table 6: Selected Cardiovascular Outcomes Per Doubling of Baseline NT-proBNP, by Alternative BMI Category</caption><thead><tr><th>Outcome and BMI Category</th><th>aHR (95% CI) per Doubling of Baseline NT-proBNP</th><th>P<sub>interaction</sub></th></tr></thead><tbody><tr><td><strong>CV Death or HF Hospitalization</strong></td><td></td><td></td></tr><tr><td>&lt;30 kg/m<sup>2</sup></td><td>1.45 (1.39 to 1.50); P&lt;0.001</td><td rowspan="3">0.001</td></tr><tr><td>≥30 to &lt;35 kg/m<sup>2</sup></td><td>1.35 (1.28 to 1.43); P&lt;0.001</td></tr><tr><td>≥35 kg/m<sup>2</sup></td><td>1.31 (1.22 to 1.41); P&lt;0.001</td></tr><tr><td><strong>HF Hospitalization</strong></td><td></td><td></td></tr><tr><td>&lt;30 kg/m<sup>2</sup></td><td>1.45 (1.38 to 1.52); P&lt;0.001</td><td rowspan="3">0.004</td></tr><tr><td>≥30 to &lt;35 kg/m<sup>2</sup></td><td>1.36 (1.28 to 1.45); P&lt;0.001</td></tr><tr><td>≥35 kg/m<sup>2</sup></td><td>1.28 (1.18 to 1.39); P&lt;0.001</td></tr></tbody></table>

aHR estimated through Cox proportional hazards regression models adjusted for age, sex, race, history of atrial fibrillation, baseline body mass index (incorporated as a spline term), estimated glomerular filtration rate (incorporated as a spline term), systolic blood pressure (incorporated as a spline term), baseline diuretic use, trial, and randomized treatment.

Abbreviations: aHR = adjusted hazard ratio; BMI = body mass index; CV = cardiovascular; HF = heart failure; NT-proBNP = N-terminal prohormone of B-type natriuretic peptide
<table><caption>Supplementary Table 7: NT-proBNP Concentrations Corresponding to Specific Rates of Clinical Outcomes Overall in Participants without Atrial Fibrillation, Stratified by Alternative Baseline Body Mass Index Categories</caption><thead><tr><th rowspan="2">Outcome and Event Rate</th><th colspan="2">Estimated NT-proBNP Concentrations (pg/mL) at Specific Event Rates, by BMI Category (kg/m²)</th></tr><tr><th>&lt;35</th><th>≥35</th></tr></thead><tbody><tr><td><strong>CV Death or HF Hospitalization</strong></td><td></td><td></td></tr><tr><td>5 per 100 person-years</td><td>450 (401, 505)</td><td>158 (103, 242)</td></tr><tr><td>10 per 100 person-years</td><td>1408 (1271, 1559)</td><td>744 (569, 972)</td></tr><tr><td><strong>HF Hospitalization</strong></td><td></td><td></td></tr><tr><td>5 per 100 person-years</td><td>980 (874, 1099)</td><td>307 (217, 435)</td></tr><tr><td>10 per 100 person-years</td><td>2856 (2443, 3334)</td><td>1415 (949, 2112)</td></tr><tr><td><strong>CV Death</strong></td><td></td><td></td></tr><tr><td>5 per 100 person-years</td><td>1366 (1201, 1554)</td><td>1280 (827, 1980)</td></tr><tr><td>10 per 100 person-years</td><td>4094 (3371, 4963)</td><td>4952 (2164, 11242)</td></tr><tr><td><strong>All-Cause Death</strong></td><td></td><td></td></tr><tr><td>5 per 100 person-years</td><td>600 (533, 675)</td><td>502 (376, 670)</td></tr><tr><td>10 per 100 person-years</td><td>2038 (1786, 2325)</td><td>2026 (1290, 3177)</td></tr></tbody></table>

Event rates estimated through Poisson regression. Uncertainty intervals NT-proBNP values reflect values of NT-proBNP at the lower and upper bounds of the 95% CI of the specified incidence rate.

Abbreviations: BMI = body mass index; CV = cardiovascular; HF = heart failure; NT-proBNP = N-terminal pro-B-type natriuretic peptide
<figure><img src="image_12.png" /><figcaption>Supplementary Figure 1: Scatterplot of Baseline BMI and Log-Transformed NT-proBNP</figcaption></figure>

Individual-level data for baseline log-transformed NT-proBNP according to baseline BMI.
Abbreviations: BMI = body mass index; NT-proBNP = N-terminal pro-B-type natriuretic peptide
<figure><img src="image_13.png" /><figcaption>Supplementary Figure 2: Continuous Flexible Association Between BMI and NT-proBNP at
Baseline, According to Age, Sex, and Race</figcaption></figure>

Figures show restricted cubic splines (3 knots) demonstrating the continuous flexible association between baseline BMI and mean (95% CI) NT-proBNP values according to age category (A), sex (B), and self-reported race (C), estimated through linear regression with adjustment for age (for B), sex (for A and C), self-reported race (for A-B), history of atrial fibrillation, estimated glomerular filtration rate (incorporated as a spline term), systolic blood pressure (incorporated as a spline term), baseline diuretic use, trial, and randomized treatment.

Abbreviations: BMI = body mass index; NT-proBNP = N-terminal pro-B-type natriuretic peptide
<figure><img src="image_14.png" /><figcaption>Supplementary Figure 3: Continuous Flexible Association Between BMI and NT-proBNP at Baseline, According to History of Atrial Fibrillation</figcaption></figure>

Figures show restricted cubic splines (3 knots) demonstrating the continuous flexible association between baseline BMI and mean (95% CI) NT-proBNP values according to history of AF, overall (A), in PARAGON-HF and DELIVER (B), and in I-Preserve and TOPCAT-Americas (C), estimated through linear regression with adjustment for age, sex, self-reported race, estimated glomerular filtration rate (incorporated as a spline term), systolic blood pressure (incorporated as a spline term), baseline diuretic use, trial, and randomized treatment.
Abbreviations: AF = atrial fibrillation; BMI = body mass index; NT-proBNP = N-terminal pro-B-type natriuretic peptide
<figure><img src="image_15.png" /><figcaption>**Supplementary Figure 4: NT-proBNP and Clinical Outcomes, by Baseline BMI Category, Excluding TOPCAT-Americas**</figcaption></figure>

Figures show the association between doubling of NT-proBNP values with CV death or HF hospitalization (A), HF hospitalization (B), CV death (C), and all-cause death (D) according to baseline BMI category after exclusion of TOPCAT-Americas. Adjusted hazard ratios (with 95% CI) estimated through Cox proportional hazards regression models, using BMI 18.5 to <25 kg/m² and NT-proBNP = 500 pg/mL as reference, presented using linear models with adjustment for age, sex, race, history of atrial fibrillation, estimated glomerular filtration rate (incorporated as a spline term), systolic blood pressure (incorporated as a spline term), baseline diuretic use, trial, and randomized treatment.
Abbreviations: BMI = body mass index; CV = cardiovascular; HF = heart failure; NT-proBNP = N-terminal pro-B-type natriuretic peptide
<caption>**Supplementary Figure 5: NT-proBNP and Clinical Outcomes According to Alternative BMI Subgroups**</caption>

<figure><img src="image_16.png" /><figcaption>B: HF Hospitalization</figcaption></figure>

<figure><img src="image_17.png" /><figcaption>C: CV Death</figcaption></figure>

<figure><img src="image_18.png" /><figcaption>D: All-Cause Death</figcaption></figure>

<figure><img src="image_19.png" /></figure>

Figures show the association between doubling of NT-proBNP values with CV death or HF hospitalization (A), HF hospitalization (B), CV death (C), and all-cause death (D) using alternative thresholds for BMI subgrouping. Adjusted hazard ratios (with 95% CI) estimated through Cox proportional hazards regression models, using BMI 18.5 to <25 kg/m² and NT-proBNP = 500 pg/mL as reference, presented using linear models with adjustment for age, sex, race, history of atrial fibrillation, estimated glomerular filtration rate (incorporated as a spline term), systolic blood pressure (incorporated as a spline term), baseline diuretic use, trial, and randomized treatment.

Abbreviations: BMI = body mass index; CV = cardiovascular; HF = heart failure; NT-proBNP = N-terminal pro-B-type natriuretic peptide
<figure><img src="image_20.png" /><figcaption>Supplementary Figure 6: Continuous Flexible Associations Between BMI, NT-proBNP, and Incidence of Selected Clinical Outcomes According to History of Atrial Fibrillation</figcaption></figure>

Contour plots show the predicted incidence rates (per 100 person-years) for CV death (A) and HF hospitalization (B) for participants without a history of AF, and for CV death (C) and HF hospitalization (D) for participants with a history of AF, at any given level of BMI or NT-proBNP. Predicted incidence rates estimated through Poisson regression, using the overall mean pooled trial population age of 72 years, and adjusted for sex. Scatterplot showing individual-level data additionally provided for reference.

Abbreviations: AF = atrial fibrillation; BMI = body mass index; CV = cardiovascular; HF = heart failure; NT-proBNP = N-terminal pro-B-type natriuretic peptide
<caption>Supplementary Figure 7: Predicted Incidence Rates of HF Hospitalization at Recent Trial NT-proBNP Eligibility Thresholds, by Baseline BMI Category</caption>

<figure><img src="image_21.png" /><figcaption>B: Predicted IR at NT-proBNP = 600 pg/mL, Among Participants with AF</figcaption></figure>

<figure><img src="image_22.png" /></figure>

Figures show predicted incidence rates (per 100 py) of HF hospitalization according to NT-proBNP eligibility thresholds recently employed in HFmrEF/HFpEF clinical trials for individuals without (A) and with a history of AF (B), by baseline BMI category. Incidence rates (and 95% CI) estimated through Poisson regression, adjusted for age, sex, and eGFR.

Abbreviations: BMI = body mass index; CV = cardiovascular; eGFR = estimated glomerular filtration rate; HF = heart failure; IR = incidence rate; NT-proBNP = N-terminal pro-B-type natriuretic peptide; py = person-years
Supplementary Figure 8: Predicted Incidence Rates of CV Death at Recent Trial NT-proBNP Eligibility Thresholds, by Baseline BMI Category

A: Predicted IR at NT-proBNP = 300 pg/mL, Among Participants without AF

<figure><img src="image_23.png" /></figure>

B: Predicted IR at NT-proBNP = 600 pg/mL, Among Participants with AF

<figure><img src="image_24.png" /></figure>

Figures show predicted incidence rates (per 100 py) of CV death according to NT-proBNP eligibility thresholds recently employed in HFmrEF/HFpEF clinical trials for individuals without (A) and with a history of AF (B), by baseline BMI category. Incidence rates (and 95% CI) estimated through Poisson regression, adjusted for age, sex, and eGFR.

Abbreviations: BMI = body mass index; CV = cardiovascular; eGFR = estimated glomerular filtration rate; HF = heart failure; IR = incidence rate; NT-proBNP = N-terminal pro-B-type natriuretic peptide; py = person-years
Supplementary Figure 9: Predicted Incidence Rates of Outcomes at Recent Trial NT-
proBNP Eligibility Thresholds, Alternative BMI Categories

A: Predicted IR at NT-proBNP = 300 pg/mL, Among Participants without AF

<figure><img src="image_25.png" /></figure>

Figures show predicted incidence rates (per 100 py) of each outcome according to according to NT-proBNP eligibility thresholds recently employed in HFmrEF/HFpEF clinical trials for individuals without atrial fibrillation. Incidence rates (and 95% CI) estimated through Poisson regression, adjusted for age, sex, and eGFR.

Abbreviations: ACM = all-cause mortality; AF = atrial fibrillation; BMI = body mass index; CVD = cardiovascular death; eGFR = estimated glomerular filtration rate; HHF = heart failure hospitalization; IR = incidence rate; NT-proBNP = N-terminal pro-B-type natriuretic peptide; py = person-years
Supplementary Figure 10: Predicted Incidence Rates of CV Death or HF Hospitalization at Recent Trial NT-proBNP Eligibility Thresholds by Baseline BMI Category, Restricting to I-Preserve and TOPCAT-Americas Alone

A: Predicted IR at NT-proBNP = 300 pg/mL, Among Participants without AF

<figure><img src="image_26.png" /></figure>

B: Predicted IR at NT-proBNP = 600 pg/mL, Among Participants with AF

<figure><img src="image_27.png" /></figure>

Figures show predicted incidence rates (per 100 py) of CV death or HF hospitalization according to NT-proBNP eligibility thresholds recently employed in HFmEF/HFpEF clinical trials for individuals without (A) and with a history of AF (B), by baseline BMI category. Restricted to I-Preserve and TOPCAT-Americas. Incidence rates (and 95% CI) estimated through Poisson regression, adjusted for age, sex, and eGFR.
Abbreviations: BMI = body mass index; CV = cardiovascular; eGFR = estimated glomerular filtration rate; HF = heart failure; IR = incidence rate; NT-proBNP = N-terminal pro-B-type natriuretic peptide; py = person-years
Supplementary Figure 11: Predicted Incidence Rates of Clinical Outcomes at Recently Proposed BMI-Based Rule-In NT-proBNP Thresholds

<figure><img src="image_28.png" /><figcaption>B: Predicted IR at NT-proBNP = 220 pg/mL, Among Participants with BMI ≥35 kg/m²</figcaption></figure>

<figure><img src="image_29.png" /></figure>

Figures show predicted incidence rates (per 100 py) of each outcome according to recently recommended BMI-based NT-proBNP rule-in criteria, among participants without a history of atrial fibrillation. Incidence rates (and 95% CI) estimated through Poisson regression, adjusted for age, sex, and eGFR.
Abbreviations: ACM = all-cause mortality; BMI = body mass index; CVD = cardiovascular death; eGFR = estimated glomerular filtration rate; HHF = heart failure hospitalization; IR = incidence rate; NT-proBNP = N-terminal pro-B-type natriuretic peptide; py = person-years