Hao-Sheng Ni, Li-Yuan Zhang, Han-Qiang Lu, Zhi-Cun Zhang, Min Zhang, Mei-Ping Lu, Lei Cheng
Peripheral blood eosinophil count is a poor surrogate for local tissue inflammation in CRSwNP. Substantial regional, temporal, and socioeconomic heterogeneity underscores the need to consider geographic context when interpreting eosinophil-based biomarkers in clinical assessment and disease stratification.
BACKGROUND: Eosinophilic inflammation is a key feature of chronic rhinosinusitis with nasal polyps (CRSwNP); however, the extent to which peripheral blood eosinophil counts reflect local nasal eosinophilia remains controversial, particularly across different geographic regions and socioeconomic contexts.
METHODS: We conducted a multicenter retrospective study involving 1047 patients with CRSwNP who underwent endoscopic sinus surgery at 3 tertiary hospitals in Jiangsu Province, China. Peripheral blood eosinophil counts and nasal mucosa eosinophil counts from polyp tissue were measured at 3 time points (2008, 2012, and 2016). Correlation analyses, receiver operating characteristic (ROC) curve analysis, linear regression models, and linear mixed-effects models were used to evaluate the association between blood and tissue eosinophil counts, as well as their temporal and regional variability. City-level gross domestic product (GDP) and annual mean PM2.5 concentrations were incorporated to explore potential socioeconomic and environmental associations.
RESULTS: Peripheral blood eosinophil counts showed a weak correlation with nasal mucosa eosinophil counts (ρ = 0.28) and had limited predictive value for CRSwNP (AUC = 0.607). Eosinophil levels varied significantly across hospitals and time points, with no consistent temporal trends observed. Linear regression analysis revealed a modest overall association between peripheral blood and nasal mucosa eosinophil counts (adjusted R2 = 0.053). Linear mixed-effects models confirmed heterogeneous temporal trends in both blood and tissue eosinophil counts across hospitals (P < 0.01). Additionally, city-level analyses revealed positive correlations between mean peripheral blood eosinophil counts and total GDP (ρ = 0.80, P = 0.014) and between nasal mucosa eosinophil counts and GDP per capita (ρ = 0.72, P = 0.037). In contrast, annual mean PM2.5 concentration was not significantly associated with either peripheral blood or nasal mucosa eosinophil counts.
CONCLUSION: Peripheral blood eosinophil count is a poor surrogate for local tissue inflammation in CRSwNP. Substantial regional, temporal, and socioeconomic heterogeneity underscores the need to consider geographic context when interpreting eosinophil-based biomarkers in clinical assessment and disease stratification.