Atherosclerotic cardiovascular disease (CVD) has been long considered an inflammatory disease. Detection of residual vascular inflammation has been considered as the ‘Holy Grail’ in CVD, which could flag those patients needing aggressive treatment to prevent plaque rupture and acute coronary syndromes (1). This notion of cause-and-effect between inflammation and CVD has been demonstrated for the first time in recent randomized clinical trials, showing that anti-inflammatory treatment e.g., by canakinumab or colchicine, leads to reduction of CVD risk in high-risk patients (2-4). Nonetheless, one of the major problems for the tailored administration of anti-inflammatory treatments has been the lack of metrics for vascular inflammation quantification. Traditionally, measurement of vascular inflammation has been based upon the measurements of circulating (plasma) biomarkers of inflammation or more recently to imaging biomarkers.
Despite the wide use of vascular inflammation biomarkers in clinical research, important questions remain unanswered regarding the added prognostic value of biomarkers of vascular inflammation over traditional clinical risk factors, as well as their comparative assessment.
In one of the largest meta-analysis in the field of vascular inflammation and CVD, Antonopoulos et al. screened >100,000 articles to explore the added value of vascular inflammation biomarkers in CVD risk prognostication (5). The selected biomarkers included in the meta-analysis were common circulating plasma biomarkers of inflammation i.e., C-reactive protein, interleukin-6 and tumor necrosis factor-a, arterial uptake of 18F-fluorodeoxyglucose (18F-FDG) by PET/CT, and coronary computed tomography (CCTA)-derived biomarkers of vascular inflammation including anatomical high-risk plaque (HRP) features and perivascular fat imaging (i.e. perivascular Fat Attenuation Index). The main endpoint was the difference in c-index (Δ[c-index]) i.e, the change in the area under the curve with the use of inflammatory biomarkers on top of the clinical risk profile +/-atherosclerosis extent for major adverse cardiovascular events (MACEs) and mortality. Whilst both plasma and imaging biomarkers of inflammation improved risk discrimination for MACEs, the increase in delta(c-index) was only marginal for plasma biomarkers, while CCTA-related biomarkers were associated with the highest added prognostic value for MACEs: HRP 5.8%, 95%CI 0.6-11.0, and PVAT (on top of coronary atherosclerosis extent and HRP): 8.2%, 95%CI 4.0-12.5).
This meta-analysis is important, as is the first systematic investigation of added prognostic value of inflammation biomarkers. The findings of the meta-analysis show that the use biomarkers of vascular inflammation (particularly the use of imaging biomarkers) may be a rational strategy to improve cardiovascular risk discrimination. Measuring of vascular inflammation in clinical practice could help guiding the personalized deployment of novel high-cost anti-inflammatory treatments for the prevention of CVD. Although the overall effect size of these approaches in risk prognostication remains to be seen, existing data suggest that inflammation-based risk stratification strategies could have a substantial impact on alleviating coronary heart disease burden. The exact clinical settings on which the use biomarkers of vascular inflammation may provide the maximum clinical benefit requires further investigation.