Heart failure & cardiomyopathiesDiagnostic or prognostic study
Proteomic markers enhance mortality prediction in heart failure
- Prognostic cohort study
- registry-based
- external validation in UK Biobank heart failure (HF) subset
Authors' conclusion
A proteomic score was the strongest molecular predictor of mortality in HF. Integrating proteomic signatures with clinical risk factors significantly improved risk prediction.
Study context
- Population
- Patients with HF in the Global Congestive Heart Failure (G-CHF) registry with genotyping, DNA methylation and proteomic profilingG-CHF registry
- Participants
- 2,432 patients
- Comparison
- Molecular risk scores added to clinical predictors
- Outcome
- All-cause mortality
- Follow-up
- Median 3.0 years
Performance
As reported in the abstract
- Deaths (all-cause)
- 523 (7.64 per 100 PY)
- ProteomicDeath23, HR per 1 SD (strongest independent predictor)
- 2.23
- NT-proBNP, HR
- 2.00
- MRSMortality, HR
- 1.66
- PRSmetaCVD, HR
- 1.10
- MAGGIC score, HR
- 1.70
- ProteomicDeath23 + MAGGIC + NT-proBNP model, C-index (highest discrimination)
- 0.77
Further findings
Incremental discrimination over proteomic-clinical model
- Adding MRSMortality, ΔC-index (small improvement)
- +0.004, P = .0039
- Adding PRSmetaCVD: no incremental benefit
Mortality across ProteomicDeath23 tertiles, low NT-proBNP/MAGGIC score (subgroup)
- Mortality rate rose across tertiles (per 100 PY)
- 1.71 to 8.12
UKB-HF validation cohort
- Consistent results
Original publication
Proteomic markers enhance mortality prediction in heart failure. Eur Heart J. Published 8 July 2026. doi:10.1093/eurheartj/ehag525
Summarised from the published abstract; every number is checked against it