Head-to-head comparison of fibrosis biomarkers ST2 and Gal-3 in chronic HF revealed superiority of ST2 over Gal-3 in risk stratification. The incremental predictive contribution of Gal-3 to existing clinical risk factors was trivial.

Identification of circulating neprilysin in HF patients and the positive association of neprilysin with cardiovascular mortality and morbidity further support the importance of NEP inhibition for augmenting natriuretic peptides as a therapeutic target.

AimsTo address the incremental usefulness of biomarkers from different disease pathways for predicting risk of death in heart failure (HF). Methods and resultsWe used data from consecutive patients treated at a structured multidisciplinary HF unit to investigate whether a combination of biomarkers reflecting ventricular fibrosis, remodelling, and stretch [ST2 and N-terminal pro brain natriuretic peptide (NTproBNP)] improved the risk stratification of a HF patient beyond an assessment based on established mortality risk factors (age, sex, ischaemic aetiology, left ventricular ejection fraction, New York Heart Association functional class, diabetes, glomerular filtration rate, sodium, haemoglobin, and beta-blocker and angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker treatments). ST2 was measured with a novel highsensitivity immunoassay. During a median follow-up time of 33.4 months, 244 of the 891 participants in the study (mean age 70.2 years at baseline) died. In the multivariable Cox proportional hazards model, both ST2 and NTproBNP significantly predicted the risk of death. The individual inclusion of ST2 and NTproBNP in the model with established mortality risk factors significantly improved the C statistic for predicting death [0.79 (0.76-0.81); P , 0.001]. The net improvement in reclassification after the separate addition of ST2 to the model with established risk factors and NTproBNP was estimated at 9.90% [95% confidence interval (CI) 4.34-15.46; P , 0.001] and the integrated discrimination improvement at 1.54 (95% CI 0.29 -2.78); P ¼ 0.015). ConclusionsOur data suggest that in a real-life cohort of HF patients, the addition of ST2 and NTproBNP substantially improves the risk stratification for death beyond that of a model that is based only on established mortality risk factors.--

BackgroundA combination of clinical and routine laboratory data with biomarkers reflecting different pathophysiological pathways may help to refine risk stratification in heart failure (HF). A novel calculator (BCN Bio-HF calculator) incorporating N-terminal pro B-type natriuretic peptide (NT-proBNP, a marker of myocardial stretch), high-sensitivity cardiac troponin T (hs-cTnT, a marker of myocyte injury), and high-sensitivity soluble ST2 (ST2), (reflective of myocardial fibrosis and remodeling) was developed.MethodsModel performance was evaluated using discrimination, calibration, and reclassification tools for 1-, 2-, and 3-year mortality. Ten-fold cross-validation with 1000 bootstrapping was used.ResultsThe BCN Bio-HF calculator was derived from 864 consecutive outpatients (72% men) with mean age 68.2±12 years (73%/27% New York Heart Association (NYHA) class I-II/III-IV, LVEF 36%, ischemic etiology 52.2%) and followed for a median of 3.4 years (305 deaths). After an initial evaluation of 23 variables, eight independent models were developed. The variables included in these models were age, sex, NYHA functional class, left ventricular ejection fraction, serum sodium, estimated glomerular filtration rate, hemoglobin, loop diuretic dose, β-blocker, Angiotensin converting enzyme inhibitor/Angiotensin-2 receptor blocker and statin treatments, and hs-cTnT, ST2, and NT-proBNP levels. The calculator may run with the availability of none, one, two, or the three biomarkers. The calculated risk of death was significantly changed by additive biomarker data. The average C-statistic in cross-validation analysis was 0.79.ConclusionsA new HF risk-calculator that incorporates available biomarkers reflecting different pathophysiological pathways better allowed individual prediction of death at 1, 2, and 3 years.