AUTHOR=He Qiang , Wang Zhen , Mei Jie , Xie Chengxin , Sun Xin
TITLE=Relationship between systemic immune-inflammation index and osteoarthritis: a cross-sectional study from the NHANES 2005–2018
JOURNAL=Frontiers in Medicine
VOLUME=11
YEAR=2024
URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2024.1433846
DOI=10.3389/fmed.2024.1433846
ISSN=2296-858X
ABSTRACT=ObjectiveThe study aimed to explore the relationship between systemic inflammatory response index (SIRI) levels and osteoarthritis (OA) using cross-sectional data from the National Health and Nutrition Examination Survey (NHANES) database from 2005 to 2018.
MethodsUsing cross-sectional data from the NHANES database from 2005 to 2018, we included 11,381 study participants divided into OA (n = 1,437) and non-OA (n = 9,944) groups. Weighted multivariable regression models and subgroup analyses were employed to investigate the relationship between SIRI and OA. Additionally, restricted cubic spline models were used to explore nonlinear relationships.
ResultsThis study enrolled 11,381 participants aged ≥20 years, including 1,437 (14%) with OA. Weighted multivariable regression analysis in the fully adjusted Model 3 indicated a correlation between higher levels of SIRI (log2-transformed) and an increased OA risk (odds ratio: 1.150; 95% confidence interval: 1.000–1.323, p < 0.05). Interaction tests showed that the variables did not significantly affect this correlation (p for interaction all >0.05). Additionally, a restricted cubic spline model revealed a nonlinear relationship between log2(SIRI) and OA risk, with a threshold effect showing 4.757 as the critical value of SIRI. SIRI <4.757 showed almost unchanged OA risk, whereas SIRI >4.757 showed rapidly increasing OA risk.
ConclusionThe positive correlation between SIRI and OA risk, with a critical value of 4.757, holds clinical value in practical applications. Additionally, our study indicates that SIRI is a novel, clinically valuable, and convenient inflammatory biomarker that can be used to predict OA risk in adults.