Han Lu, Bi Lei, Li Xinpeng
Department of Clinical Laboratory, Public Health Clinical Center of Chengdu, Chengdu, China.
PLoS One. 2025 Sep 11;20(9):e0332105. doi: 10.1371/journal.pone.0332105. eCollection 2025.
Blood-cell-based inflammatory biomarkers are increasingly recognized for their diagnostic value in infections due to their clinical accessibility. With Hepatitis C virus (HCV) incidence rising and its often asymptomatic onset, this study aims to improve diagnostic evidence for HCV by analyzing changes in these biomarkers.
Utilizing NHANES database, we employed binary logistic regression and generalized additive models to explore the relationship between systemic inflammatory index and HCV infection. Three adjusted models controlled for confounders, and subgroup analyses were stratified by age, gender, race, and BMI.
Significant differences were observed in PLR (103.24 ± 44.59), SII (455.23 ± 339.56), PNR (58.22 ± 32.20), PMR (366.85 ± 191.76), and NMR (7.03 ± 3.78) between infected and uninfected groups (P < 0.05). Adjusted analyses revealed associations between anti-HCV and Log2-PLR (OR = 0.58), Log2-SII (OR = 0.64), Log2-PMR (OR = 0.77), and Log2-NMR (OR = 0.79). Individuals under 30 showed no significant differences. A unit increase below 9.30 in Log2-PMR reduced HCV risk by 0.60-fold. PMR demonstrated an AUC of 0.648, specificity 0.7632, and sensitivity 0.4709.
In individuals aged 30 and above, inflammatory markers PLR, SII, PMR, and NMR decrease in HCV cases. Variability across races, genders, and BMI groups highlights their diagnostic utility in diverse populations.
基于血细胞的炎症生物标志物因其临床可及性，在感染诊断价值方面日益受到认可。随着丙型肝炎病毒（HCV）发病率上升且其发病常无症状，本研究旨在通过分析这些生物标志物的变化来改善HCV的诊断证据。
利用美国国家健康与营养检查调查（NHANES）数据库，我们采用二元逻辑回归和广义相加模型来探究全身炎症指数与HCV感染之间的关系。三个调整模型对混杂因素进行了控制，亚组分析按年龄、性别、种族和体重指数（BMI）进行分层。
感染组与未感染组在血小板与淋巴细胞比率（PLR，103.24±44.59）、全身炎症反应指数（SII，455.23±339.56）、中性粒细胞与淋巴细胞比率（PNR，58.22±32.20）、血小板与单核细胞比率（PMR，366.85±191.76）和中性粒细胞与单核细胞比率（NMR，7.03±3.78）方面存在显著差异（P<0.05）。调整分析显示抗HCV与Log2-PLR（比值比[OR]=0.58）、Log2-SII（OR=0.64）、Log2-PMR（OR=0.77）和Log2-NMR（OR=0.79）之间存在关联。30岁以下个体无显著差异。Log2-PMR低于9.30时，每增加一个单位，HCV风险降低0.60倍。PMR的曲线下面积（AUC）为0.648，特异性为0.7632，敏感性为0.4709。
在30岁及以上个体中，HCV病例的炎症标志物PLR、SII、PMR和NMR降低。不同种族、性别和BMI组之间的变异性突出了它们在不同人群中的诊断效用。
