Abstract
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.