Head-to-head comparison of 2 myocardial fibrosis biomarkers for long-term heart failure risk stratification: ST2 versus galectin-3

Abstract

Objectives: ST2 and galectin-3 (Gal-3) were compared head-to-head for long-term risk stratification in an ambulatory heart failure (HF) population on top of other risk factors including N-terminal pro-B-type natriuretic peptide.

Background: ST2 and Gal-3 are promising biomarkers of myocardial fibrosis and remodeling in HF.

Methods: This cohort study included 876 patients (median age: 70 years, median left ventricular ejection fraction: 34%). The 2 biomarkers were evaluated relative to conventional assessment (11 risk factors) plus N-terminal pro-B-type natriuretic peptide in terms of discrimination, calibration, and reclassification analysis. Endpoints were 5-year all-cause and cardiovascular mortality, and the combined all-cause death/HF hospitalization.

Results: During a median follow-up of 4.2 years (5.9 for alive patients), 392 patients died. In bivariate analysis, Gal-3 and ST2 were independent variables for all endpoints. In multivariate analysis, only ST2 remained independently associated with cardiovascular mortality (hazard ratio: 1.27, 95% confidence interval [CI]: 1.05 to 1.53, p = 0.014). Incorporation of ST2 into a full-adjusted model for all-cause mortality (including clinical variables and N-terminal pro-B-type natriuretic peptide) improved discrimination (C-statistic: 0.77, p = 0.004) and calibration, and reclassified significantly better (integrated discrimination improvement: 1.5, 95% CI: 0.5 to 2.5, p = 0.003; net reclassification index: 9.4, 95% CI: 4.8 to 14.1, p < 0.001). Incorporation of Gal-3 showed no significant increase in discrimination or reclassification and worse calibration metrics. On direct model comparison, ST2 was superior to Gal-3.

Conclusions: 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.

Keywords: AIC; Akaike information criterion; BIC; Bayesian information criterion; CI; Gal-3; HF; HR; IDI; IQR; LVEF; N-terminal pro–B-type natriuretic peptide; NRI; NT-proBNP; ST2; biomarkers; confidence interval; galectin-3; hazard ratio; heart failure; high-sensitivity soluble ST2; integrated discrimination improvement; interquartile range; left ventricular ejection fraction; myocardial fibrosis; net reclassification improvement; remodeling; survival.