Association of systemic inflammation index with psoriasis risk and psoriasis severity: A retrospective cohort study of NHANES 2009 to 2014

医学 银屑病 回顾性队列研究 银屑病面积及严重程度指数 逻辑回归 队列研究 队列 内科学 免疫学
作者
Huan-huan Guo,Ruo-xi Chen
出处
期刊:Medicine [Ovid Technologies (Wolters Kluwer)]
卷期号:103 (8): e37236-e37236 被引量:3
标识
DOI:10.1097/md.0000000000037236
摘要

To investigate the association of systemic inflammation index (SII) with psoriasis risk and psoriasis severity. This is a retrospective cohort study based on data from the National Health and Nutrition Examination Survey database from 2009 to 2014. The psoriasis information was obtained from the questionnaire data, and the SII was calculated as neutrophil × platelet/lymphocyte. We performed matching by controlling age and gender to reach a 1:2 ratio for better statistical power. Weighted logistic regression analysis, subgroup analysis, restricted cubic spline analysis, and threshold analysis were used to evaluate the association of SII with psoriasis risk. Besides, mediation analysis was conducted to assess the possible regulatory path. Finally, the receiver operating characteristic curve was plotted to analyze the predictive value of SII for psoriasis severity. The study involved 16,466 participants including 16,020 no-psoriasis participants and 446 psoriasis participants. After matching, psoriasis and non-psoriasis individuals were 446 and 892, respectively. SII was significantly higher in the psoriasis group than the non-psoriasis group ( P < .05). Additionally, white blood cells and monocytes were significantly linked to psoriasis risk and SII scores ( P < .05). Besides, SII elevation was an independent predictor for upregulated psoriasis risk ( P < .05). There was a nonlinear relationship between SII and psoriasis risk ( P nonlinear < .05), which was not mediated by white blood cells and monocytes. Unexpectedly, SII had no significance in predicting SII severity ( P > .05). SII can independently predict psoriasis risk but has no impact on psoriasis severity. Further, SII serves as a potential and robust biomarker for identifying high-risk psoriasis individuals.
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