PROGNOSTIC VALUE OF HIGH-SENSITIVITY C-REACTIVE PROTEIN (HS-CRP) IN PREDICTING FUTURE CARDIOVASCULAR EVENTS: A SYSTEMATIC REVIEW AND META-ANALYSIS

Abstract

Therapeutic Area

CVD Prevention – Primary and Secondary

Background

Inflammation plays a central role in atherosclerosis and cardiovascular events. High-sensitivity C-reactive protein (hs-CRP), a ubiquitous biomarker of systemic inflammation, has come to the attention of preventive cardiologists for its ability to enhance cardiovascular risk prediction beyond established risk factors. But its prognostic significance in heterogeneous populations and study designs is uncertain. To fill this gap, we performed a systematic review and meta-analysis to investigate association between a high hs-CRP level and subsequently increased risk for future cardiovascular events in adults.

Methods

This study adhered to the PRISMA 2020 statement and was registered in PROSPERO (CRD42025638183). A systematic search of studies from 2013 to 2023 yielded 3,644 articles; after 248 duplicates were removed, data were extracted from full-text reviews of 30. Four studies (n=6816) met inclusion criteria for quantitative analysis. We included studies that reported odds ratios (OR) with confidence intervals (CIs) for the association between elevated hs-CRP and cardiovascular events. We performed a random-effects meta-analysis to derive pooled effect estimates.

Results

They included four studies with 6,816 subjects. Elevated hs-CRP levels predicted subsequent cardiovascular events (OR: 1.99, 95% CI: 1.36–2.94, p = 0.0004). Moderate heterogeneity was found (I² = 66.1%, p = 0.0315). The individual study ORs ranged from 1.50 to 4.50 and were all statistically significant. Outcomes were asymptomatic carotid stenosis, aortic atherosclerosis, ischemic stroke, and restenosis after coronary angioplasty.

Conclusions

High hs-CRP is an independent risk factor for cardiovascular events, with those affected being almost twice as likely to suffer them. These findings solidify its role as an adjunct biomarker in preventive cardiology. Larger and more homogenous studies are needed to improve the risk prediction models including inflammation, as the traits of inflammation may vary in different populations.