Biomarker-Informed Phenotyping of the Heart Failure Continuum: A Population-Based Evaluation of the Second Universal Definition of Heart Failure

Objective: To develop and evaluate a biomarker-informed, computable phenotype of the heart failure (HF) continuum, aligned with 2026 AHA/ACC/ESC/WHF Expert Consensus, using NHANES and linked mortality data, and to determine whether this phenotype identifies subgroups with distinct mortality risks. Methods: We analyzed 11,477 U.S. adults aged ≥20 years from the 1999-2004 NHANES cycles who participated in the surplus-sera biomarker substudy and were linked to National Death Index follow-up. Participants were classified into four phenotypes according to the 2026 Universal Definition of Heart Failure: no apparent risk, Stage A (at risk), Stage B (elevated NT-proBNP without self-reported HF), and Stage C (self-reported HF). Survey-weighted Kaplan-Meier curves and nested, multiply imputed Cox proportional hazards models, with sequential adjustment for demographic, socioeconomic, and cardiometabolic covariates, were used to estimate associations with mortality. Pairwise phenotype comparisons, standardized adjusted survival estimates, and restricted mean survival times were also calculated. Incremental prognostic value was evaluated by comparing discrimination and reclassification metrics between the full phenotype and a conventional three-level model that excluded NT-proBNP. Results: Weighted prevalences were 16.9%, 70.0%, 10.7%, and 2.4% for no apparent risk, Stage A, Stage B, and Stage C, respectively. In fully adjusted models, the hazard ratios (HRs) relative to no apparent risk were 1.58 (95% CI, 1.08-2.30), 2.88 (95% CI, 2.00-4.16), and 2.56 (95% CI, 1.61-4.09), respectively. Stage B was associated with significantly higher mortality risk than Stage A (HR, 1.83; 95% CI, 1.62-2.07), whereas the difference between Stage C and Stage B was not statistically significant (HR, 0.89; 95% CI, 0.71-1.11). The association for Stage B attenuated less across sequentially adjusted models than that for Stage C. Adjusted 10-year mortality risks were 15.2% for Stage B and 14.2% for Stage C. Incorporating Stage B into the conventional model yielded only marginal improvements in discrimination (ΔC-statistic, 0.002; 95% CI, 0.001-0.002). Conclusion: A biomarker-informed phenotype of the HF continuum can be operationalized using national survey data and identifies a pre-HF subgroup with an adjusted mortality risk not significantly different from that of individuals with overt HF, despite only marginal gains in prognostic discrimination.

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Publication Details

Journal
medRxiv
Published
2026-11-06
DOI
https://doi.org/10.64898/2026.11.04.26367312
Primary Topic
Heart Failure Treatment and Management
Type
preprint
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preprint

Biomarker-Informed Phenotyping of the Heart Failure Continuum: A Population-Based Evaluation of the Second Universal Definition of Heart Failure

Jiancheng Ye, Haoxin Chen
medRxiv
Heart Failure Treatment and Management
preprint

Biomarker-Informed Phenotyping of the Heart Failure Continuum: A Population-Based Evaluation of the Second Universal Definition of Heart Failure

Jiancheng Ye, Haoxin Chen
preprint en

Abstract

Objective: To develop and evaluate a biomarker-informed, computable phenotype of the heart failure (HF) continuum, aligned with 2026 AHA/ACC/ESC/WHF Expert Consensus, using NHANES and linked mortality data, and to determine whether this phenotype identifies subgroups with distinct mortality risks. Methods: We analyzed 11,477 U.S. adults aged ≥20 years from the 1999-2004 NHANES cycles who participated in the surplus-sera biomarker substudy and were linked to National Death Index follow-up. Participants were classified into four phenotypes according to the 2026 Universal Definition of Heart Failure: no apparent risk, Stage A (at risk), Stage B (elevated NT-proBNP without self-reported HF), and Stage C (self-reported HF). Survey-weighted Kaplan-Meier curves and nested, multiply imputed Cox proportional hazards models, with sequential adjustment for demographic, socioeconomic, and cardiometabolic covariates, were used to estimate associations with mortality. Pairwise phenotype comparisons, standardized adjusted survival estimates, and restricted mean survival times were also calculated. Incremental prognostic value was evaluated by comparing discrimination and reclassification metrics between the full phenotype and a conventional three-level model that excluded NT-proBNP. Results: Weighted prevalences were 16.9%, 70.0%, 10.7%, and 2.4% for no apparent risk, Stage A, Stage B, and Stage C, respectively. In fully adjusted models, the hazard ratios (HRs) relative to no apparent risk were 1.58 (95% CI, 1.08-2.30), 2.88 (95% CI, 2.00-4.16), and 2.56 (95% CI, 1.61-4.09), respectively. Stage B was associated with significantly higher mortality risk than Stage A (HR, 1.83; 95% CI, 1.62-2.07), whereas the difference between Stage C and Stage B was not statistically significant (HR, 0.89; 95% CI, 0.71-1.11). The association for Stage B attenuated less across sequentially adjusted models than that for Stage C. Adjusted 10-year mortality risks were 15.2% for Stage B and 14.2% for Stage C. Incorporating Stage B into the conventional model yielded only marginal improvements in discrimination (ΔC-statistic, 0.002; 95% CI, 0.001-0.002). Conclusion: A biomarker-informed phenotype of the HF continuum can be operationalized using national survey data and identifies a pre-HF subgroup with an adjusted mortality risk not significantly different from that of individuals with overt HF, despite only marginal gains in prognostic discrimination.

medRxiv
Cornell University (US)
Good health and well-being
Heart Failure Treatment and Management
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