Heart Failure Risk Assessment Using Biomarkers in Patients With Atrial Fibrillation: Analysis From COMBINE-AF

Paul M. Haller, MD, PHD; Petr Jarolim, MD, PHD; Michael G. Palazzolo, MSC; Andrea Bellavia, PHD; Elliott M. Antman, MD; John Eikelboom, MBBS, MSC; Christopher B. Granger, MD; Josephine Harrington, MD; Jeff S. Healey, MD; Ziad Hijazi, MD, PHD; Manesh R. Patel, MD; Siddharth M. Patel, MD, MPH; Christian T. Ruff, MD, MPH; Lars Wallentin, MD, PHD; Eugene Braunwald, MD; Robert P. Giugliano, MD, SM; David A. Morrow, MD, MPH

Disclosures

J Am Coll Cardiol. 2024;84(16)

Abstract

Background: Heart failure (HF) is common among patients with atrial fibrillation (AF), and accurate risk assessment is clinically important.

Objectives: The goal of this study was to investigate the incremental prognostic performance of N-terminal pro–B-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-cTnT), and growth differentiation factor (GDF)-15 for HF risk stratification in patients with AF.

Methods: Individual patient data from 3 large randomized trials comparing direct oral anticoagulants (DOACs) with warfarin (ARISTOTLE [Apixaban for Reduction in Stroke and Other Thromboembolic Events in Atrial Fibrillation], ENGAGE AF-TIMI 48 [Effective Anticoagulation With Factor Xa Next Generation in Atrial Fibrillation–Thrombolysis In Myocardial Infarction 48], and RE-LY [Randomized Evaluation of Long-Term Anticoagulation Therapy]) from the COMBINE-AF (A Collaboration Between Multiple Institutions to Better Investigate Non-Vitamin K Antagonist Oral Anticoagulant Use in Atrial Fibrillation) cohort were pooled; all patients with available biomarkers at baseline were included. The composite endpoint was hospitalization for HF (HHF) or cardiovascular death (CVD), and secondary endpoints were HHF and HF-related death. Cox regression was used, adjusting for clinical factors, and interbiomarker correlation was addressed using weighted quantile sum regression analysis.

Results: In 32,041 patients, higher biomarker values were associated with a graded increase in absolute risk for CVD/HHF, HHF, and HF-related death. Adjusting for clinical variables and all biomarkers, NT-proBNP (HR per 1 SD: 1.68; 95% CI: 1.59-1.77), hs-cTnT (HR: 1.39; 95% CI: 1.33-1.44), and GDF-15 (HR: 1.20; 95% CI: 1.15-1.25) were significantly associated with CVD/HHF. The discrimination of the clinical model improved significantly upon addition of the biomarkers (c-index: 0.70 [95% CI: 0.69-0.71] to 0.77 [95% CI: 0.76-0.78]; likelihood ratio test, P &t; 0.001). Using weighted quantile sum regression analysis, the contribution to risk assessment was similar for NT-proBNP and hs-cTnT for CVD/HHF (38% and 41%, respectively); GDF-15 provided a statistically significant but lesser contribution to risk assessment. Results were similar for HHF and HF-related death, individually, and across key subgroups of patients based on a history of HF, AF pattern, and reduced or preserved left ventricular ejection fraction.

Conclusions: NT-proBNP, hs-cTnT, and GDF-15 contributed significantly and independently to the risk stratification for HF endpoints in patients with AF, with hs-cTnT being as important as NT-proBNP for HF risk stratification. Our findings support a possible future use of these biomarkers to distinguish patients with AF at low or high risk for HF.

Introduction

Heart failure (HF) and atrial fibrillation (AF) commonly occur concurrently. The population prevalence for HF is an anticipated >8 million individuals in the United States by 2030, and the lifetime risk ranges from 20% to 46%.1 Meanwhile, the population prevalence for AF is an anticipated >12 million individuals in the United States by 2030, and the lifetime risk is approximately 30%.^[1,2] In patients with new-onset HF, about one-third have a history of AF, with many subsequently developing AF. In addition, about 1 in 10 patients with new-onset AF has a history of HF.^[1,3,4]

The interplay between HF and AF extends beyond their frequent co-occurrence. HF fosters AF, through the proposed mechanisms of sustained elevation of intra-atrial pressure, myocardial fibrosis, and electrical remodeling.^[2,5] AF, in turn, impairs myocardial function, not only through immediate changes in left ventricular filling but also via atrial and ventricular fibrosis and activation of the renin-angiotensinaldosterone system over time.^[5] In addition, the intertwined relationship between AF and HF is also evident from studies showing that genetic variants associated with HF predict future AF, supporting the concept of AF as an extension of a myopathy.^[6]

Identifying patients with AF at increased risk for HF is important. In fact, in patients with AF, incident HF events surpass the risk for thromboembolism and are the most common major cardiovascular events and indication for hospitalization.^[7,8,9] Several agents with proven benefit for reducing the risk of new or recurrent HF-related events are recommended by current guidelines for patients with reduced or preserved ejection fraction.^[10,11] In addition, several studies have also highlighted the effect of HF therapies in reducing AF burden.^[12] Moreover, specifically for patients with AF, increasing evidence points toward the superiority of an early rhythm control strategy over standard of care for the reduction of cardiovascular death and HF-related events as shown in EAST-AFNET 4 (Early Treatment of Atrial Fibrillation for Stroke Prevention Trial).^[13] This finding aligns with the observation that the progression of AF is associated with higher event rates.^[8,14] Effective strategies to mitigate incident HF in patients with AF,^[13] along with the availability of effective agents for the treatment of HF,^[10,11] set the stage for a potential new era of HF prevention and early intervention in this growing population. As such, accurate HF risk assessment in patients with AF is needed.

Prior studies have proposed circulating biomarkers as a tool for HF risk assessment in AF. In particular, natriuretic peptides have been established for the diagnostic and prognostic assessment of HF.^[10,11] In addition, cardiac troponins, which identify myocardial damage,^[15] and growth differentiation factor (GDF)-15, which is associated with inflammation and fibrosis, have been repeatedly linked to the prevalence and incidence of HF.^[16,17] Thus, the aim of the current study was to investigate the following: 1) improvement in risk stratification comparing models with biomarkers and models with clinical variables alone in a large cohort of patients with AF; 2) delineation of the independent contribution of each biomarker compared with the others; and 3) assessment of the risk relationships between these biomarkers and outcomes within important subgroups.

1 2 3 4 5

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Abstract and Introduction
Methods
Results
Discussion
Conclusions
References

Table 1. Patient Characteristics (N = 32,041)
Age, y	71 (64-77)
Male	63.3 (20,288)
White	84.5 (27,058/32,039)
Body mass index, kg/m²	28.5 (25.4-32.5)
Diabetes mellitus	27.4 (8,782)
Hypertension	87.4 (28,005)
Established coronary artery disease	31.8 (10,183/32,030)
Prior myocardial infarction	14.3 (4,592/32,033)
Prior stroke	13.3 (4,265)
History of congestive heart failure	41.6 (13,317)
Left ventricular ejection fraction ≥50%	69.1 (14,849/21,493)
Valvular disease	19.7 (6,309/32,033)
Persistent/permanent atrial fibrillation	77.0 (24,669/32,032)
Paroxysmal atrial fibrillation	23.0 (7,363/32,032)
CHADS²-VASC score	4 (3-5)
Creatinine clearance, mL/min	71.9 (55.3-92.4)
NT-proBNP, ng/L	760 (376-1,351)
hs-cTnT, ng/mL	12 (8.1-18.5)
hs-cTnT >14 ng/mL^a	40.1 (12,838)
GDF-15, ng/mL	1,495 (1,060-2,201)

Values are median (Q1-Q3), % (n), or % (n/N). Data available in overall study population if not otherwise stated. ^aThe high-sensitivity cardiac troponin T (hs-cTnT) 14 ng/mL value represents the 99th percentile upper reference limit for this assay.

GDF = growth differentiation factor; NT-proBNP = N-terminal pro–B-type natriuretic peptide.

Authors and Disclosures

Paul M. Haller, MD, PHD,^a,b Petr Jarolim, MD, PHD,^c Michael G. Palazzolo, MSC,^a Andrea Bellavia, PHD,^a,d Elliott M. Antman, MD,^e John Eikelboom, MBBS, MSC,^f,g Christopher B. Granger, MD,^h Josephine Harrington, MD,^h Jeff S. Healey, MD,^f,g Ziad Hijazi, MD, PHD,ⁱ Manesh R. Patel, MD,^h Siddharth M. Patel, MD, MPH,^a Christian T. Ruff, MD, MPH,^a Lars Wallentin, MD, PHD,ⁱ Eugene Braunwald, MD,^a Robert P. Giugliano, MD, SM,^a David A. Morrow, MD, MPH^a

From the ^aTIMI Study Group, Division of Cardiovascular Medicine, Brigham & Women’s Hospital, and Harvard Medical School, Boston, Massachusetts, USA; ^bDepartment of Cardiology, University Heart and Vascular Center Hamburg, Hamburg, Germany; ^cDepartment of Pathology, Brigham & Women’s Hospital, Boston, Massachusetts, USA; ^dDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA; ^eDivision of Cardiovascular Medicine, Brigham & Women’s Hospital, and Harvard Medical School, Boston, Massachusetts, USA; ^fPopulation Health Research Institute, Hamilton, Ontario, Canada; ^gMcMaster University, Hamilton, Ontario, Canada; ^hDepartment of Medicine, Division of Cardiology, Duke University, Durham, North Carolina, USA; and the ⁱDepartment of Medical Sciences and Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden.

FUNDING SUPPORT AND AUTHOR DISCLOSURES: Dr Haller is supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)–10086/1-1. Dr S.M. Patel is supported by a T32 postdoctoral training grant from the National Heart, Lung, and Blood Institute (NHLBI) (T32HL007604). RE-LY was funded by Boehringer Ingelheim, ARISTOTLE was funded by Bristol Myers Squibb and Pfizer, and ENGAGE AF-TIMI 48 was funded by Daiichi-Sankyo. No outside funding was obtained to support the creation of the COMBINE AF database or for these analyses. Dr Haller has received travel grants from the German Center of Cardiovascular Research (DZHK); and has received funding by the German Foundation for Heart Research and the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)–10086/1-1. Dr Jarolim has received research support through BWH from Abbott Laboratories, Amgen, Inc, AstraZeneca, LP, Daiichi-Sankyo, Roche Diagnostic Corporation, and Siemens Healthineers. Dr Antman received grants from Daiichi-Sankyo during the conduct of the study. Mr Eikelboom has received honoraria and/or research support from Anthos, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Idorsia, Janssen, Merck, and Pfizer. Dr Granger has received consulting fees from AbbVie, Abiomed, Alnylam Pharmaceuticals, Amgen, Anthos, Bayer Corporation, Boehringer Ingelheim, Boston Scientific Corporation, Bristol Myers Squibb, Cardionomic, CeleCor Therapeutics, Janssen Pharmaceutical, Merck, Novo Nordisk, Novartis, Pfizer, Philips, and Roche; has salary funded by Duke grants sponsored by Alnylam Pharmaceuticals, Boehringer Ingelheim, Bristol Myers Squibb, Janssen Pharmaceuticals, NHLBI, Novartis, Pfizer, and Philips; and has equity in tenac.io. Dr Healey has received research grants and speaking fees from Boston Scientific, Medtronic, Bristol Myers Squibb/Pfizer, and Servier; and has been a consultant for Bayer. Dr Hijazi has received lecture and consulting fees from Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Pfizer, and Roche Diagnostics; and has received research support from Hjärt-Lungfonden (The Swedish Heart-Lung Foundation and Uppsala University Hospital). Dr M.R. Patel has received consulting fees from Bayer, Janssen, and Novartis; and has received research grants from the NHLBI, Bayer, Novartis, and Philips. Dr S.M. Patel has received consulting fees from Janssen. Dr Ruff has received research grants through Brigham and Women’s Hospital from Anthos, AstraZeneca, Daiichi-Sankyo, Janssen, and Novartis; and has received honoraria for scientific advisory boards and consulting from Anthos, Bayer, Bristol Myers Squibb, Daiichi-Sankyo, Janssen, and Pfizer. Dr Wallentin has received institutional research grants from Bristol Myers Squibb/Pfizer, AstraZeneca, GlaxoSmithKline, Boehringer Ingelheim, and Roche Diagnostics; and is a patent holder on GDF-15 for prognostication in acute coronary syndrome. Dr Braunwald has received research grants through his institution from AstraZeneca, Daiichi-Sankyo, Merck, and Novartis; and has consulted for Amgen, Bristol Myers Squibb, Boehringer Ingelheim, Cardurion, Edgewise, and Verve. Dr Giugliano has received research support from Anthos Therapeutics and Daiichi- Sankyo; has received honoraria for lectures from Daiichi-Sankyo, Medical Education Resources (MER), Menarini, Pfizer, SAJA Pharmaceuticals, Servier, and Shanghai Medical Telescope; and has received consulting fees from Artivion, Inc, AstraZeneca, Bayer, Daiichi- Sankyo, Perosphere, PhaseBio Pharmaceuticals, Samsung, Sanofi, Syneos Health, and Thrombosis Research Institute. Dr Morrow has received consulting fees from Abbott Laboratories, ARCA Biopharma, InCarda, Inflammatix, Merck & Co, Novartis, and Roche Diagnostics. Dr Haller, Dr Morrow, Mr Palazzolo, Dr Bellavia, Dr Ruff, Dr Braunwald, and Dr Giugliano are members of the TIMI Study Group, which has received institutional research grant support through Brigham and Women’s Hospital from Abbott, Amgen, Anthos Therapeutics, AstraZeneca, Bayer HealthCare Pharmaceuticals, Inc, Daiichi-Sankyo, Eisai, Intarcia, MedImmune, Merck, Novartis, Pfizer, Quark Pharmaceuticals, Regeneron Pharmaceuticals, Inc, Roche, Siemens Healthcare Diagnostics, Inc, The Medicines Company, and Zora Biosciences. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

ADDRESS FOR CORRESPONDENCE: Dr David A. Morrow, TIMI Study Office, 60 Fenwood Road, Suite 7022-7024W, Boston, Massachusetts 02115, USA. E-mail: dmorrow@partners.org. X handle: @PaulMHaller, @TimiStudyGroup.