PubMed HealthSearch

PubMed · 41903165

EMPEROR-Preserved Risk Model and Outcomes in the FINEARTS-HF Trial: A Prespecified Secondary Analysis of FINEARTS-HF.

Abstract

IMPORTANCE: Patients with heart failure (HF) and mildly reduced ejection fraction (HFmrEF) or preserved EF (HFpEF) show substantial heterogeneity in prognosis. OBJECTIVES: To evaluate the performance of biomarker-driven prognostic models derived from the Empagliflozin Outcome Trial in Patients With Chronic Heart Failure With Preserved Ejection Fraction (EMPEROR-Preserved) Trial in the Finerenone Trial to Investigate Efficacy and Safety Superior to Placebo in Patients With Heart Failure (FINEARTS-HF) and to examine whether baseline risk modified the therapeutic effect of finerenone. DESIGN, SETTING, AND PARTICIPANTS: This is a prespecified secondary analysis of the FINEARTS-HF trial, which was conducted across 653 sites in 37 countries among adults aged 40 years and older with symptomatic HF and left ventricular EF (LVEF) of 40% or greater. Patients were randomized between September 2020 and January 2023, and data analysis for this study was conducted from September to October 2025. The median (IQR) follow-up period was 32 (23-37) months. INTERVENTION: Finerenone (titrated to 20 mg or 40 mg) or placebo. MAIN OUTCOMES AND MEASURES: EMPEROR-Preserved risk scores for the outcomes of first HF hospitalization or cardiovascular death, cardiovascular death, and all-cause death were calculated in FINEARTS-HF using models incorporating N-terminal pro-B-type natriuretic peptide, high-sensitivity cardiac troponin T, New York Heart Association functional class, history of chronic obstructive pulmonary disease and diabetes, insulin use, and-depending on outcome-age, hemoglobin and albumin levels, HF duration, time from prior HF hospitalization, and sodium-glucose transporter 2 inhibitor use. Estimated risks were compared with observed event rates, and model performance was assessed using Harrell C statistic. Treatment effects were evaluated across risk quintiles (Q1 to Q5) and across the continuous risk distribution. RESULTS: Among 6001 patients (mean [SD] age, 72.0 [9.6] years; 2732 [45.5%] women; 3003 randomized to finerenone and 2998 randomized to placebo), the EMPEROR-Preserved risk model estimated risk of outcomes, with Q5 vs Q1 hazard ratios (HRs) of 10.49 (95% CI, 8.14-13.52) for the composite of HF hospitalization or cardiovascular death and 13.47 (95% CI, 8.79-20.64) for cardiovascular death. The model demonstrated good discrimination. The treatment effect of finerenone was consistent across risk quintiles for first HF hospitalization or cardiovascular death (Q1: HR, 0.93 [95% CI, 0.58-1.49]; Q2: HR, 1.04 [95% CI, 0.76-1.43]; Q3: HR, 0.82 [95% CI, 0.62-1.07]; Q4: HR, 0.81 [95% CI, 0.65-1.01]; and Q5: HR, 0.88 [95% CI, 0.74-1.05]; P for interaction = .68) and remained uniform across the continuous risk spectrum. CONCLUSIONS AND RELEVANCE: The EMPEROR-Preserved risk models demonstrated good performance in FINEARTS-HF. Baseline risk did not modify the relative treatment effect of finerenone. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04435626.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Misato Chimura, Kirsty McDowell, Pardeep S Jhund, Alasdair D Henderson, Brian L Claggett, Akshay S Desai, Meike Brinker, James Lay-Flurrie, Andrea Glasauer, Laura Goea, Mario Berger, Carolyn S P Lam, Michele Senni, Adriaan A Voors, Faiez Zannad, Bertram Pitt, Muthiah Vaduganathan, Scott D Solomon, John J V McMurray. 2026-05-01. EMPEROR-Preserved Risk Model and Outcomes in the FINEARTS-HF Trial: A Prespecified Secondary Analysis of FINEARTS-HF.. https://doi.org/10.1001/jamacardio.2026.1049

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans