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Published on: January 28, 2020
Inflammatory cytokines as biomarkers in heart failure
Thor Ueland1, Lars Gullestad2, Ståle H Nymo3
1Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, Norway; Faculty of Medicine, University of Oslo, Norway; K.G. Jebsen Inflammatory Research Center, University of Oslo, Norway; KG Jebsen Thrombosis Research and Expertise Center, N-9037 Tromsø, Norway.
Abstract:
Inflammation has been implicated in the pathogenesis of heart failure (HF). In addition to their direct involvement as mediators in the pathogenesis of HF, inflammatory cytokines and related mediators could also be suitable markers for risk stratification and prognostication in HF patients. Many reports have suggested that inflammatory cytokines may predict adverse outcome in these patients. However, most studies have been limited in sample size and lacking full adjustment with the most recent and strongest biochemical predictor such as NT-proBNP and high sensitivity troponins. Furthermore, a number of pre-analytical and analytical aspects of cytokine measurements may limit their use as biomarkers. This review focuses on technical, informative and practical considerations concerning the clinical use of inflammatory cytokines as prognostic biomarkers in HF. We focus on the predictive value of tumor necrosis factor (TNF) α, the TNF family receptors sTNFR1 and osteoprotegerin, interleukin (IL)-6 and its receptor gp130, the chemokines MCP-1, IL-8, CXCL16 and CCL21 and the pentraxin PTX-3 in larger prospective fully adjusted studies. No single inflammatory cytokine provides sufficient discrimination to justify the transition to everyday clinical use as a prognosticator in HF. However, while subjecting potential new HF markers to rigorous comparisons with "gold-standard" markers, such as NT-proBNP, using receiver operating characteristics (ROCs) and HF risk models, makes sense from a clinical standpoint, it may pose a threat to a broadening of mechanistic insight if the new markers are dismissed solely on account of lower statistical power.
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