P427A multi-biomarker score improves long-term prediction of mortality in patients with advanced heart failure

    loading  Checking for direct PDF access through Ovid

Abstract

Purpose

Accurate risk prediction is important for an adequate management of heart failure (HF) patients. We assessed the incremental prognostic ability of a multi-biomarker approach in advanced HF.

Methods and Results

In 349 patients with advanced HF (71.9 ± 12.6 years, 66% male) we analyzed plasma levels of growth differentiation factor 15 (GDF-15), high sensitive tumor necrosis factor-alpha (hsTNF-α), myeloperoxidase, monocyte chemoattractant protein 1 (MCP-1), fractalkine, macrophage colony-stimulating factor (M-CSF), high sensitive granulocyte colony-stimulating factor (hsG-CSF), hepatocyte growth factor (HGF), pigmentepithelium-derived factor (PEDF), soluble apoptosis-stimulating fragment (sFAS), soluble tumor necrosis factor-related apoptosis-inducing ligand (sTRAIL) and soluble tumor necrosis factor-like weak inducer of apoptosis (sTWEAK). These biomarkers have previously been proposed to be involved in different pathophysiological pathways of HF including inflammation, immunological activation, oxidative stress, cell growth, remodeling, angiogenesis and apoptosis. During a median follow-up of 4.9 years (IQR4.6-5.2) 55.9% of patients died. Using multivariable Cox regression and variable selection by bootstrapping techniques, the following five novel biomarkers were retained in the best mortality prediction model in addition to age and N-terminal pro-B-type natriuretic peptide (NT-proBNP): the chemokine fractalkine, the anti-apoptotic and pro-hypertrophic GDF-15, the angiogenic, mitogenic and antifibrotic HGF and the two pro-apoptotic molecules sFAS and sTRAIL. This multi-biomarker score had strong discriminatory power for 5-year survival (area under Receiver Operating Characteristic curve (AUC) = 0.80) and was significantly better than a conventional risk score including known clinical predictors and NT-proBNP (AUC = 0.75, P = 0.04). A simplified multi-biomarker score including the seven selected variables as categorical variables still had a strong discriminatory ability (AUC = 0.79).

Conclusions

Risk prediction by a multi-biomarker score is superior to a conventional risk score including clinical parameters and NT-proBNP. Additional predictive information from different biological pathways reflects the multi-systemic character of HF. The newly described predictive role of fractalkine supports the involvement of immunological mechanisms in HF pathology.

Related Topics

    loading  Loading Related Articles