COPD増悪における炎症反応：C反応性タンパク質の臨床的および予測的役割

Acute exacerbations of chronic obstructive pulmonary disease (ECOPD) are pivotal events that accelerate lung function decline, impair quality of life, and increase the risk of hospitalization and mortality. Beyond episodic airway deterioration, ECOPD should be conceptualized as a systemic inflammatory syndrome driven by dysregulated responses to infectious or environmental triggers. Among inflammatory biomarkers, C-reactive protein (CRP) is the most extensively studied in ECOPD because of its rapid kinetics, wide availability, and clinical accessibility. This narrative review aims to summarize the diagnostic, therapeutic, and prognostic role of CRP in ECOPD. CRP levels rise sharply during exacerbations, particularly in pneumonic events, supporting diagnostic stratification and differentiation from non-bacterial or eosinophilic phenotypes. When inegrated with clinical assessment, CRP improves diagnostic accuracy and informs antibiotic stewardship; CRP-guided strategies have been shown to reduce unnecessary antibiotic use without compromising clinical outcomes. Elevated CRP at presentation is associated with greater exacerbation severity, increased need for ventilatory support, and longer hospital stay. Persistently elevated CRP at discharge is linked to early relapse and readmission, while higher levels have also been associated with thromboembolic and cardiovascular risk, highlighting the systemic consequences of ECOPD. Despite these advantages, CRP is inherently nonspecific, influenced by comorbidities and timing of measurement, and optimal thresholds vary across clinical settings. CRP is a robust and accessible biomarker that provides valuable diagnostic, therapeutic, and prognostic information in ECOPD. Its incorporation into routine clinical practice can improve patient stratification, support antibiotic stewardship, and enhance monitoring of individuals at high-risk of adverse outcomes. Future advances are likely to rely on longitudinal interpretation of CRP and its integration into multimarker panels and predictive models, combined with clinical variables and digital health data, to enable phenotype-driven management and precision medicine approaches in ECOPD.