Multimarker approach including CRP, sST2 and GDF-15 for prognostic stratification in stable heart failure

Abstract

Aims: Inflammation and cardiac remodelling are common and synergistic pathways in heart failure (HF). Emerging biomarkers such as soluble suppression of tumorigenicity 2 (sST2) and growth differentiation factor-15 (GDF-15), which are linked to inflammation and fibrosis process, have been proposed as prognosis factors. However, their potential additive values remain poorly investigated.

Methods and results: Here, we aimed at evaluating inflammatory and remodelling biomarkers to predict both short-term and long-term mortality in a population with chronic HF in comparison with other classical clinical or biological markers (i.e. N terminal pro brain natriuretic peptide, hs-cTnT, C-reactive protein) alone or using meta-analysis global group in chronic HF risk score in a cohort of 182 patients followed during 80 months (interquartile range: 12.3-90.0). Proportional hazard assumption does not hold for sST2 and C-reactive protein, and follow-up was split into short term (less than 1 year), midterm (between 1 and 5 years), and long term (after 5 years). In univariate analysis, C-reactive protein and sST2 were predictive of short-term mortality but not of middle term and long term whereas GDF-15 was predictive of short and mid-term but not of long-term mortality. In a multivariate model after adjustment for meta-analysis global group in chronic HF score including the three markers, only sST2 was predictive of short-term mortality (P = 0.0225), and only GDF-15 was predictive of middle term mortality (P = 0.0375). None of the markers was predictive of long-term mortality.

Conclusions: Our results demonstrate that both sST2 and GDF-15 significantly improve the prognosis evaluation of HF patients and suggest that the value of GDF-15 is more sustained overtime and could predict middle term events.

Keywords: Biomarkers; C-reactive protein; GDF-15; Heart failure; Hs-troponin; NT-proBNP; Prognosis; sST2.

Figure 1

Kaplan–Meier curves for all‐cause mortality based on quartiles of C‐reactive protein, soluble suppression of tumorigenicity 2, and growth differentiation factor‐15.

Figure 2

Test of the proportional hazard assumption of Cox regression for C‐reactive protein, soluble suppression of tumorigenicity 2, and growth differentiation factor‐15. Schoenfeld residuals were computed to test proportional hazard assumption. P values indicate significant correlations between Schoenfeld residuals and time for C‐reactive protein and soluble suppression of tumorigenicity 2 (A–B). This correlation is not significant for growth differentiation factor‐15 (C).

Figure 3

Multivariate Cox model after Akaike's information criterion‐based feature selection. Coloured rectangles indicate biomarker‐associated hazard ratios; each biomarker has been assessed for short‐term, middle‐term, and long‐term prediction of mortality. CRP, C‐reactive protein; GDF‐15, growth differentiation factor‐15; LVEF, left ventricular ejection fraction; MAGGIC, meta‐analysis global group in chronic heart failure; MRA, mineralocorticoid receptor antagonist; sST2, soluble suppression of tumorigenicity 2