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Arthritis Res Ther
关节炎治疗研究 - v.25; 2023
- PMC9985219IF: 4.9 Q2 B2 PMC9985219IF:4.9 Q2
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Arthritis Res Ther.2023; 25: 34.
doi: 10.1186/s13075-023-03018-6IF: 4.9 Q2
PMCID: PMC9985219IF:4.9 Q2
The association between systemic immune-inflammation index and rheumatoid arthritis: evidence from NHANES 1999–2018
全身免疫炎症指数与类风湿性关节炎之间的关联:1999-2018 年 NHANES 提供的证据
Bo Liu
1Department of Orthopaedics, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015 China
Jie Wang
1Department of Orthopaedics, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015 China
Yan-yan Li
2Department of Integrated Traditional Chinese and Western Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, China
Kang-peng Li
1Department of Orthopaedics, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015 China
Qiang Zhang
1Department of Orthopaedics, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015 China
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Associated Data 相关数据
- Data Availability Statement
数据可用性声明 Publicly available datasets were analyzed in this study. This data can be found here: The National Health and Nutrition Examination Survey dataset at https://www.cdc.gov/nchs/nhanes/index.htm
Abstract 摘要
Purpose 目的
We aimed to explore the relationship between the systemic immune-inflammation index (SII) and rheumatoid arthritis (RA) using NHANES from 1999 to 2018.
我们旨在利用 1999 年至 2018 年的美国国家健康调查(NHANES),探讨全身免疫炎症指数(SII)与类风湿性关节炎(RA)之间的关系。
Methods 方法
We collected data from the NHANES database from 1999 to 2018. The SII is calculated from the counts of lymphocytes (LC), neutrophils (NC), and platelets (PC). The RA patients were derived from questionnaire data. We used weighted multivariate regression analysis and subgroup analysis to explore the relationship between SII and RA. Furthermore, the restricted cubic splines were used to explore the non-linear relationships.
我们从 NHANES 数据库中收集了 1999 年至 2018 年的数据。SII由淋巴细胞(LC)、中性粒细胞(NC)和血小板(PC)的计数计算得出。RA 患者来自问卷调查数据。我们使用加权多元回归分析和亚组分析来探讨 SII 与 RA 之间的关系。此外,我们还使用了限制性三次样条来探讨非线性关系。
Result 结果
Our study included a total of 37,604 patients, of which 2642 (7.03%) had rheumatoid arthritis. After adjusting for all covariates, the multivariate logistic regression analysis showed that high SII (In-transform) levels were associated with an increased likelihood of rheumatoid arthritis (OR=1.167, 95% CI=1.025–1.328, P=0.020). The interaction test revealed no significant effect on this connection. In the restricted cubic spline regression model, the relationship between ln-SII and RA was non-linear. The cutoff value of SII for RA was 578.25. The risk of rheumatoid arthritis increases rapidly when SII exceeds the cutoff value.
我们的研究共纳入 37 604 名患者,其中 2642 人(7.03%)患有类风湿性关节炎。在对所有协变量进行调整后,多变量逻辑回归分析表明,SII(In-transform)水平高与类风湿性关节炎的可能性增加有关(OR=1.167,95% CI=1.025-1.328,P=0.020)。交互检验显示,这种联系没有明显影响。在限制性三次样条回归模型中,ln-SII 与 RA 之间的关系是非线性的。RA 的 SII 临界值为 578.25。当 SII 超过临界值时,患类风湿性关节炎的风险会迅速增加。
Conclusion 结论
In general, there is a positive correlation between SII and rheumatoid arthritis. Our study shows that SII is a novel, valuable, and convenient inflammatory marker that can be used to predict the risk of rheumatoid arthritis in US adults.
一般来说,SII 与类风湿性关节炎呈正相关。我们的研究表明,SII 是一种新颖、有价值且方便的炎症标记物,可用于预测美国成年人患类风湿性关节炎的风险。
关键词: 系统免疫炎症指数 类风湿性关节炎 NHANES 关系 一项横断面研究
Introduction 导言
Rheumatoid arthritis (RA) is a chronic systemic inflammatory autoimmune disease characterized by diffuse polyarthritis and infiltration of pro-inflammatory cytokines [1, 2]. Joint fever, swelling and pain, pannus formation, and cartilage degeneration and bone erosion are the three classic pathological features of RA, as well as other systemic symptoms outside the joints, such as rash, fever, muscle loss, and weakness [3, 4]. RA is more common in women in their 40s. Previous studies have shown that the pathogenesis of rheumatoid arthritis is complex. At the cellular level, it is mainly manifested by an imbalance between osteoblasts and osteoclasts, excessive proliferation of synoviocytes, and immune cell dysfunction [5]. The cellular inflammatory factors can also lead to rheumatoid arthritis, such as interleukin (IL)-17, tumor necrosis factor (TNF-α), IL-6, and IL-8 [6, 7]. Recent studies have shown that the emergence of autoreactive T cells is a crucial pathological event in patients with RA [7]. Primitive CD4 T cells differentiate into pro-inflammatory helper T cells, which are more easily able to invade tissues and cause inflammation through immune cell death [7–9].
类风湿性关节炎(RA)是一种以弥漫性多关节炎和促炎细胞因子浸润为特征的慢性全身炎症性自身免疫性疾病[ 1, 2]。关节发热、肿胀和疼痛、脓肿形成、软骨变性和骨侵蚀是 RA 的三大典型病理特征,同时还伴有关节以外的其他全身症状,如皮疹、发热、肌肉萎缩和乏力等 [ 3, 4]。RA 多见于 40 多岁的女性。以往的研究表明,类风湿性关节炎的发病机制十分复杂。在细胞层面,主要表现为成骨细胞和破骨细胞之间的失衡、滑膜细胞过度增殖以及免疫细胞功能失调[5]。细胞炎症因子也可导致类风湿性关节炎,如白细胞介素(IL)-17、肿瘤坏死因子(TNF-α)、IL-6 和 IL-8[6,7]。最近的研究表明,自反应性 T 细胞的出现是 RA 患者的一个重要病理现象[7]。原始的CD4 T细胞分化为促炎性辅助T细胞,这些细胞更容易入侵组织,并通过免疫细胞死亡引起炎症[7- 9]。
Systemic immune-inflammation index (Sll), as an evaluation index of systemic inflammatory response, has been confirmed to be related to the prognosis of elderly patients with digestive system tumors [10, 11]. It is calculated using a formula that takes into account the levels of certain immune system markers in the blood, The calculation formula is platelets × neutrophils ÷ lymphocytes [11]. The SII is often used as a predictor of mortality in patients with tumors, as higher SII values have been associated with an increased risk of death [10, 12, 13]. This may be related to the imbalance between the body’s tumor-promoting and anti-tumor factors in the tumor state. When the imbalance occurs, neutrophils and platelets increase, lymphocytes decrease, and the level of SII also increases. In recent years, the application field of SII has been expanding continuously, and more studies have shown that SII can also be used to predict the severity of certain diseases and monitor treatment effects [14–18].
全身免疫炎症指数(Sll)作为全身炎症反应的评价指标,已被证实与老年消化系统肿瘤患者的预后有关[10, 11]。其计算公式为血小板 × 中性粒细胞 ÷ 淋巴细胞[11]。SII 常被用作预测肿瘤患者死亡率的指标,因为 SII 值越高,死亡风险越大[10, 12, 13]。这可能与肿瘤状态下体内促肿瘤因子和抗肿瘤因子之间的失衡有关。当失衡发生时,中性粒细胞和血小板增加,淋巴细胞减少,SⅡ水平也随之升高。近年来,SⅡ的应用领域不断扩大,越来越多的研究表明,SⅡ还可用于预测某些疾病的严重程度和监测治疗效果[14- 18]。
The systemic immune-inflammatory index (SII) may be useful in assessing the severity and progression of psoriasis and psoriatic arthritis (PA). In people with higher SII levels, the immune system is in a constant state of activation, leading to chronic inflammation in the joints and other tissues [19, 20]. This inflammation can damage cartilage and bone, causing pain and difficulty moving. Satis, S. et al. [21] found that the SII levels were significantly higher in patients with rheumatoid arthritis compared to healthy controls and that SII were correlated with the severity of the disease. These findings suggest that the SII may be a useful tool for monitoring inflammation and disease activity in patients with RA.
全身免疫炎症指数(SII)可用于评估银屑病和银屑病关节炎(PA)的严重程度和进展情况。在 SII 水平较高的人群中,免疫系统处于持续激活状态,导致关节和其他组织出现慢性炎症[19, 20]。这种炎症会损伤软骨和骨骼,导致疼痛和行动不便。Satis,S.等人[ 21] 发现,与健康对照组相比,类风湿性关节炎患者的 SII 水平明显更高,而且 SII 与疾病的严重程度相关。这些研究结果表明,SII 可能是监测类风湿性关节炎患者炎症和疾病活动的有用工具。
The National Health and Nutrition Examination Survey (NHANES) is a population-based cross-sectional survey designed to collect information about the health and nutrition of American households. The database uses a complex stratified, multistage probability cluster sampling design to represent the entire US population [22]. However, to date, no researchers have used the NHANES database to explore the relationship between SII and RA. Our study aimed to clarify the relationship between SII and RA in participants of the NHANES. We hypothesized that the RA patients have higher SII.
美国国家健康与营养调查(NHANES)是一项以人口为基础的横断面调查,旨在收集美国家庭的健康与营养信息。该数据库采用复杂的分层多阶段概率群组抽样设计,以代表整个美国人口[22]。然而,迄今为止,还没有研究人员利用 NHANES 数据库来探讨 SII 与 RA 之间的关系。我们的研究旨在阐明 NHANES 参与者的 SII 与 RA 之间的关系。我们假设 RA 患者的 SII 值较高。
Methods 方法
Data selection and study design
数据选择和研究设计
We download data from the NHANES database, which surveys about 5000 individuals from across the country each year. The database includes demographic data, dietary data, examination data, laboratory data, questionnaire data, and limited access data. NHANES was conducted over 10 cycles from 1999 to 2018. This research received approval from the National Center for Health Statistics Research Ethics Review Board, and participants signed informed consent forms. The detailed NHANES study design and data are publicly available at https://www.cdc.gov/nchs/nhanes/.
我们从 NHANES 数据库中下载数据,该数据库每年对全国约 5000 人进行调查。该数据库包括人口统计学数据、饮食数据、检查数据、实验室数据、问卷数据和有限访问数据。NHANES 从 1999 年到 2018 年共进行了 10 个周期。本研究获得了美国国家卫生统计中心研究伦理审查委员会的批准,参与者签署了知情同意书。详细的 NHANES 研究设计和数据可在 https://www.cdc.gov/nchs/nhanes/ 上公开获取。
Our study exclusions were as follows: (1) adults aged 18 years or older; (2) pregnant women; (3) individuals with missing data on arthritis; (4) individuals with missing data on platelets, neutrophils, and lymphocytes (Fig. (Fig.1).1). A total of 37,604 individuals were ultimately included in this study. Considering our study included hematology variables, we chose Mobile Examination Centers (MEC) weights. The weight calculation formula for 1999–2000 and 2001–2002 was 2/10 × wtmec4yr, and the weight calculation formula for 2003–2018 was 1/10 × wtmec2yr.
我们的研究排除了以下人群:(1)18 岁或以上的成年人;(2)孕妇;(3)关节炎数据缺失者;(4)血小板、中性粒细胞和淋巴细胞数据缺失者(图 1)。本研究最终共纳入 37 604 人。考虑到我们的研究包括血液学变量,我们选择了流动体检中心(MEC)的权重。1999-2000 年和 2001-2002 年的权重计算公式为 2/10 × wtmec4yr,2003-2018 年的权重计算公式为 1/10 × wtmec2yr。
The definition of systemic immune-inflammation index
全身免疫炎症指数的定义
The methods used to derive CBC parameters are based on the Beckman Coulter methodology of counting and sizing, in combination with an automatic diluting and mixing device for sample processing, and a single beam photometer for hemoglobinometry. The WBC differential uses VCS technology. The Beckman Coulter DxH 800 instrument in the NHANES mobile examination center (MEC) produces a CBC on blood specimens and provides a distribution of blood cells for all participants. According to previous research reports, the calculation formula of SII is platelet count × neutrophil count/lymphocyte count [11, 18]. In addition, SII was log2-transformed when conducting regression analysis (Fig. (Fig.2B),2B), considering that these inflammatory markers were right-skewed distributed (Fig. (Fig.22A).
用于得出 CBC 参数的方法是基于贝克曼库尔特计数和定型方法,结合用于样本处理的自动稀释和混合装置,以及用于血红蛋白测定的单光束光度计。白细胞差分仪采用 VCS 技术。NHANES 移动检查中心(MEC)的贝克曼库尔特 DxH 800 仪器可对血液标本进行全血细胞计数,并提供所有参与者的血细胞分布情况。根据以往的研究报告,SII 的计算公式为血小板计数×中性粒细胞计数/淋巴细胞计数[ 11, 18]。此外,考虑到这些炎症指标呈右斜分布,因此在进行回归分析时对 SII 进行了对数 2 转换(图(Fig.2B),2B)(图(Fig.22A)。
The definition of rheumatoid arthritis
类风湿性关节炎的定义
The diagnosis of arthritis was obtained by a self-report questionnaire (MCQ160a). Specifically, participants were asked that “Has a doctor or other health professional ever told you that you had arthritis?” The response options were “Yes” or “No.” Rheumatoid arthritis was assessed via the following question: “Which type of arthritis was it?” The response options were “Rheumatoid arthritis,” Osteoarthritis,” “Psoriatic arthritis,” “Other,” “Refused,” and “Don’t know.” A previous study demonstrated great consistency (85%) between self-reported arthritis and clinically confirmed arthritis [23].
关节炎的诊断是通过自我报告问卷(MCQ160a)获得的。具体来说,参与者被问到 "医生或其他医疗专业人员是否曾告诉过您患有关节炎?回答选项为 "是 "或 "否"。类风湿性关节炎通过以下问题进行评估:"是哪种类型的关节炎?"回答选项为 "类风湿性关节炎"、"骨关节炎"、"银屑病关节炎"、"其他"、"拒绝 "和 "不知道"。之前的一项研究表明,自我报告的关节炎与临床确诊的关节炎之间具有很高的一致性(85%)[ 23]。
The covariates 协变量
The covariates included in our study that may affect the RA include age (< 40, 40–59, ≥60), gender (male, female), race (White, Black, Mexican American, other), education (under high school, high school or equivalent, college graduate or above), poverty-to-income ratio (PIR<1.3, 1.3–3.49, >= 3.5), body mass index (<25, 25–29.9, ≥30), work activity (yes, no), smoking (never, former, current), alcohol use (never, former, mild, moderate, heavy), hypertension (yes, no), diabetes (no, pre-diabetes, diabetes), hyperlipidemia (yes, no), and complete blood count (white blood cells, red blood cells).
我们的研究中包含的可能影响 RA 的协变量包括年龄(< 40、40-59、≥60)、性别(男、女)、种族(白人、黑人、墨西哥裔美国人、其他)、教育程度(高中以下、高中或同等学历、大学毕业或以上)、贫困收入比(PIR<1.3、1.3-3.49、>= 3.5)、体重指数(<25、25-29.9、≥30)、工作活动(是、否)、吸烟(从不、曾经、现在)、饮酒(从不、曾经、轻度、中度、重度)、高血压(是、否)、糖尿病(否、糖尿病前期、糖尿病)、高脂血症(是、否)和全血细胞计数(白细胞、红细胞)。
Statistical methods 统计方法
All analyzes were performed using R (version 4.1.3, http://www.R-project.org). The NHANES database was surveyed using complex, multi-stage, sampling, therefore, our study used MEC exam weight (WTMEC4YR, WTMEC2YR) for analysis. Continuous variables are presented as weighted means and standard deviations, and categorical variables are presented as weighted percentages. We compared categorical variables and continuous variables between different groups using the chi-square test and T-test, respectively.
所有分析均使用 R(4.1.3 版,http://www.R-project.org)进行。NHANES 数据库采用复杂的多阶段抽样方法进行调查,因此我们的研究使用 MEC 考试加权(WTMEC4YR、WTMEC2YR)进行分析。连续变量以加权平均值和标准差表示,分类变量以加权百分比表示。我们分别使用卡方检验和 T 检验来比较不同组间的分类变量和连续变量。
We found that the SII data is unevenly distributed and clearly skewed to the right. Therefore, prior to conducting statistical analysis, we need to ln-transform its values. We analyzed the association of RA and SII using weighted multivariate logistic regression models. In the crude model, covariates were not adjusted. In model 1, gender, age, and race were adjusted. In model 2, age, gender, race, PIR, edu, and BMI were adjusted. Model 3 was adjusted for age, gender, race, PIR, edu, BMI, hypertension, diabetes, hyperlipidemia, alcohol user, smoke, work activity, white blood cell count, and red blood cell count. Furthermore, we considered the systemic immunity index as a categorical variable by Quartile. The restricted cubic splines were used to explore the non-linear relationships. To explore the threshold effect of In-SII on the risk of rheumatoid arthritis and to find the inflection point, we used the smooth curve fitting and generalized additive models.
我们发现,SII 数据分布不均,且明显向右倾斜。因此,在进行统计分析之前,我们需要对其数值进行 ln 变换。我们使用加权多变量逻辑回归模型分析了 RA 和 SII 的相关性。在粗模型中,协变量未作调整。在模型 1 中,对性别、年龄和种族进行了调整。在模型 2 中,对年龄、性别、种族、PIR、edu 和 BMI 进行了调整。模型 3 调整了年龄、性别、种族、PIR、教育程度、体重指数、高血压、糖尿病、高脂血症、饮酒、吸烟、工作活动、白细胞计数和红细胞计数。此外,我们还将全身免疫力指数视为四分位数的分类变量。我们使用限制性三次样条来探索非线性关系。为了探索 In-SII 对类风湿性关节炎风险的阈值效应并找到拐点,我们使用了平滑曲线拟合和广义加法模型。
Finally, we further performed stratification and interaction analyses by age, PIR, BMI, race, edu, hypertension, diabetes, hyperlipidemia, work activity, alcohol user, and smoke. All statistical tests were two-sided, and a P-value < 0.05 was statistically significant.
最后,我们进一步按照年龄、PIR、BMI、种族、教育程度、高血压、糖尿病、高脂血症、工作活动、饮酒和吸烟进行了分层和交互分析。所有统计检验均为双侧检验,P 值小于 0.05 为具有统计学意义。
Results 成果
General characteristics of the study population
研究对象的一般特征
A total of 36,463 people were included in this study, of whom 51.9% were male and 48.1% were female, 26.8% were over 60 years of age and 41.0% were white. The number of patients diagnosed with rheumatoid arthritis was 2642 (7.0%). The clinical characteristics of the participants by SII quartiles are shown in Table Table1,1, from which we can find statistically significant differences in age, gender, race, education, BMI, hypertension, diabetes, hyperlipidemia, smoking, alcohol use, and work activity (all p<0.05).
这项研究共纳入 36 463 人,其中 51.9% 为男性,48.1% 为女性,26.8% 年龄超过 60 岁,41.0% 为白人。确诊为类风湿性关节炎的患者人数为 2642 人(7.0%)。按 SII 四分位数分列的参与者临床特征见表 1,1,从中我们可以发现,在年龄、性别、种族、教育程度、体重指数、高血压、糖尿病、高脂血症、吸烟、饮酒和工作活动方面,差异有统计学意义(均 p<0.05)。
Table 1 表 1
Weighted demographic characteristics of all participants
所有参与者的加权人口特征
Variable | Total | Q1 | Q2 | Q3 | Q4 | P-value |
---|---|---|---|---|---|---|
SII | 6.181 (0.005) | 5.507 (0.004) | 5.994 (0.001) | 6.316 (0.001) | 6.806 (0.004) | < 0.0001 |
Gender | < 0.0001 | |||||
Male | 19,523 (51.917) | 5399 (57.462) | 5001 (53.229) | 4703 (50.380) | 4420 (44.756) | |
Female | 18,081 (48.083) | 4015 (42.538) | 4391 (46.771) | 4691 (49.620) | 4984 (55.244) | |
Age | < 0.0001 | |||||
Below 60 | 27,516 (73.173) | 6892 (82.354) | 6949 (82.953) | 7032 (82.786) | 6643 (80.032) | |
Over 60 | 10,088 (26.827) | 2522 (17.646) | 2443 (17.047) | 2362 (17.214) | 2761 (19.968) | |
Race | < 0.0001 | |||||
White | 15,436 (41.049) | 2842 (56.742) | 3777 (65.819) | 4222 (68.871) | 4595 (71.053) | |
Black | 7901 (21.011) | 3177 (19.964) | 1845 (10.402) | 1497 ( 8.327) | 1382 ( 7.603) | |
Mexican American 墨西哥裔美国人 | 7178 (19.088) | 1497 (8.905) | 1860 (9.461) | 1948 (9.664) | 1873 (9.001) | |
Other | 7089 (18.852) | 1898 (14.389) | 1910 (14.318) | 1727 (13.138) | 1554 (12.344) | |
Edu | < 0.0001 | |||||
Under high school 高中以下 | 9920 (26.414) | 2506 (17.438) | 2468 (16.382) | 2460 (16.301) | 2486 (16.818) | |
High school or equivalent 高中或同等学历 | 8561 (22.795) | 2063 (22.092) | 2048 (22.397) | 2177 (24.450) | 2273 (25.640) | |
College graduate or above 大专或以上学历 | 19,075 (50.791) | 4833 (60.469) | 4865 (61.221) | 4744 (59.249) | 4633 (57.542) | |
PIR | 0.055 | |||||
Below 1.3 | 10,545 (30.684) | 2659 (21.958) | 2571 (20.555) | 2602 (20.699) | 2713 (22.376) | |
1.3–3.5 | 13,049 (37.97) | 3261 (35.950) | 3247 (35.517) | 3237 (35.238) | 3304 (36.065) | |
Over 3.5 | 10,773 (31.347) | 2631 (42.091) | 2767 (43.928) | 2761 (44.064) | 2614 (41.560) | |
BMI | < 0.0001 | |||||
Below 25 | 11,841 (31.975) | 3218 (37.163) | 2977 (34.391) | 2766 (30.822) | 2880 (32.605) | |
25–30 | 12,783 (34.519) | 3316 (34.919) | 3298 (35.603) | 3244 (34.543) | 2925 (31.384) | |
Over 30 | 12,408 (33.506) | 2772 (27.918) | 3013 (30.006) | 3243 (34.635) | 3380 (36.010) | |
Hypertension | < 0.0001 | |||||
No | 23,543 (62.608) | 6017 (69.978) | 6052 (70.143) | 5923 (67.733) | 5551 (64.058) | |
Yes | 14,061 (37.392) | 3397 (30.022) | 3340 (29.857) | 3471 (32.267) | 3853 (35.942) | |
Diabetes | < 0.0001 | |||||
No | 29,412 (78.215) | 7459 (83.957) | 7362 (83.934) | 7433 (83.852) | 7158 (81.057) | |
Pre-diabetes | 2523 (6.709) | 596 (6.101) | 627 (6.013) | 639 (6.282) | 661 (6.713) | |
Diabetes | 5669 (15.076) | 1359 ( 9.942) | 1403 (10.052) | 1322 ( 9.866) | 1585 (12.230) | |
Hyperlipidemia | < 0.0001 | |||||
No | 11,672 (31.039) | 3321 (37.126) | 2899 (32.367) | 2688 (29.487) | 2764 (30.289) | |
Yes | 25,932 (68.961) | 6093 (62.874) | 6493 (67.633) | 6706 (70.513) | 6640 (69.711) | |
Alcohol use | < 0.0001 | |||||
Never | 4805 (14.232) | 1241 (12.196) | 1217 (11.216) | 1147 (10.663) | 1200 (11.052) | |
Former | 5315 (15.743) | 1282 (11.817) | 1246 (11.648) | 1313 (13.312) | 1474 (14.559) | |
Mild | 10,961 (32.465) | 2905 (36.822) | 2774 (36.178) | 2711 (34.791) | 2571 (31.805) | |
Moderate | 5191 (15.375) | 1256 (17.608) | 1332 (17.717) | 1319 (17.393) | 1284 (17.206) | |
Heavy | 7490 (22.185) | 1691 (21.557) | 1836 (23.241) | 1982 (23.841) | 1981 (25.377) | |
Smoke | < 0.0001 | |||||
Never | 21,053 (56.031) | 5508 (57.649) | 5391 (57.413) | 5271 (55.789) | 4883 (51.418) | |
Former | 8346 (22.212) | 2023 (22.562) | 2081 (22.149) | 2010 (21.402) | 2232 (23.299) | |
Now | 8175 (21.757) | 1874 (19.789) | 1912 (20.439) | 2108 (22.809) | 2281 (25.283) | |
Work activity 工作活动 | 0.006 | |||||
No | 19,774 (52.595) | 5159 (48.399) | 4875 (45.917) | 4831 (44.956) | 4909 (46.196) | |
Yes | 17,823 (47.405) | 4255 (51.601) | 4513 (54.083) | 4563 (55.044) | 4492 (53.804) | |
Arthritis | < 0.0001 | |||||
No | 34,962 (92.974) | 8806 (94.972) | 8803 (95.222) | 8780 (95.295) | 8573 (93.514) | |
Yes | 2642 (7.026) | 608 (5.028) | 589 (4.778) | 614 (4.705) | 831 (6.486) | |
White blood cell 白细胞 | 7.235 (0.025) | 6.139 (0.039) | 6.750 (0.025) | 7.357 (0.029) | 8.526 (0.035) | < 0.0001 |
Red blood cell 红血球 | 4.736 (0.006) | 4.717 (0.008) | 4.747 (0.009) | 4.755 (0.007) | 4.724 (0.009) | < 0.0001 |
Lymphocyte | 2.151 (0.009) | 2.456 (0.026) | 2.220 (0.010) | 2.094 (0.010) | 1.877 (0.009) | < 0.0001 |
Neutrophils | 4.281 (0.018) | 2.932 (0.015) | 3.747 (0.015) | 4.448 (0.018) | 5.791 (0.027) | < 0.0001 |
Platelet | 254.407 (0.655) | 209.898 (0.780) | 240.372 (0.796) | 263.130 (0.816) | 297.571 (1.011) | < 0.0001 |
Univariate logistic regression analysis of RA
RA 的单变量逻辑回归分析
Based on Table Table2,2, it can be concluded that the risk of rheumatoid arthritis is increased (OR > 1, p < 0.05) in individuals with older age (> 40 years), female, black race, high BMI (> 25), smoking, diabetes (yes), hypertension (yes), and hyperlipidemia (yes). However, participants who were Mexican-Americans, other races, PIR (> 1.3), higher education, alcohol use, and work activities (yes) show a reduced risk of rheumatoid arthritis (OR < 1, p < 0.05).
根据表 2,2,可以得出以下结论:年龄较大(> 40 岁)、女性、黑人、体重指数较高(> 25)、吸烟、糖尿病(是)、高血压(是)和高脂血症(是)的人患类风湿性关节炎的风险增加(OR > 1,P < 0.05)。然而,墨西哥裔美国人、其他种族、PIR(> 1.3)、高学历、饮酒和工作活动(是)的参与者患类风湿性关节炎的风险降低(OR < 1,P < 0.05)。
Table 2 表 2
Weighted univariate logistic analysis of RA
RA 的加权单变量逻辑分析
Character | OR 95% CI | P-value |
---|---|---|
Age | ||
Below 60 | ref | ref |
Over 60 | 4.501 (4.024, 5.034) | <0.0001 |
BMI | ||
Below 25 | ref | ref |
25–30 | 1.224 (1.064, 1.409) | 0.005 |
Over 30 | 2.018 (1.758, 2.317) | <0.0001 |
PIR | ||
Below 1.3 | ref | ref |
1.3–3.5 | 0.698 (0.601, 0.810) | <0.0001 |
Over 3.5 | 0.476 (0.406, 0.557) | <0.0001 |
Gender | ||
Male | ref | ref |
Female | 1.545 (1.377, 1.733) | <0.0001 |
Race | ||
White | ref | ref |
Black | 1.485 (1.307, 1.687) | <0.0001 |
Mexican American 墨西哥裔美国人 | 0.684 (0.580, 0.806) | <0.0001 |
Other | 0.760 (0.633, 0.912) | 0.003 |
Edu | ||
Under high school 高中以下 | ref | ref |
High school or equivalent 高中或同等学历 | 0.719 (0.631, 0.818) | <0.0001 |
College graduate or above 大专或以上学历 | 0.453 (0.391, 0.524) | <0.0001 |
Hypertension | ||
No | ref | ref |
Yes | 3.925 (3.461, 4.450) | <0.0001 |
Diabetes | ||
No | ref | ref |
Pre-diabetes | 1.753 (1.474, 2.084) | <0.0001 |
Diabetes | 3.043 (2.711, 3.416) | <0.0001 |
Hyperlipidemia | ||
No | ref | ref |
Yes | 2.041 (1.770, 2.354) | <0.0001 |
Alcohol use | ||
Never | ref | ref |
Former | 1.589 (1.341, 1.882) | <0.0001 |
Mild | 0.730 (0.612, 0.869) | <0.001 |
Moderate | 0.557 (0.453, 0.684) | <0.0001 |
Heavy | 0.511 (0.420, 0.621) | <0.0001 |
Smoke | ||
Never | ref | ref |
Former | 1.968 (1.704, 2.272) | <0.0001 |
Now | 1.626 (1.408, 1.878) | <0.0001 |
Work activity 工作活动 | ||
No | ref | ref |
Yes | 0.753 (0.678, 0.837) | <0.0001 |
SII | 1.296 (1.166, 1.441) | <0.0001 |
Relationship between RA and SII
RA 与 SII 的关系
After performing a weighted multivariate logistic regression analysis (Table (Table3),3), our results indicate that a higher SII score is associated with an increased risk of developing rheumatoid arthritis. This association was significant in our crude model (OR=1.296; 95% CI=1.166–1.441, p<0.001), model 1 (OR=1.291; 95% CI=1.164–1.433, p<0.001), and model 2 (OR=1.192; 95% CI=1.066–1.332, p=0.002). In the fully adjusted model, the positive association between SII and proteinuria remained stable (OR=1.167; 95% CI=1.025–1.328, p=0.020), indicating that for every unit increase in In-SII score, the risk of developing rheumatoid arthritis increased by 17%.
在进行加权多变量逻辑回归分析后(表 3),我们的结果表明,SII 分数越高,患类风湿性关节炎的风险越高。在我们的粗略模型(OR=1.296;95% CI=1.166-1.441,p<0.001)、模型 1(OR=1.291;95% CI=1.164-1.433,p<0.001)和模型 2(OR=1.192;95% CI=1.066-1.332,p=0.002)中,这种关联都很明显。在完全调整模型中,SII 与蛋白尿之间的正相关关系保持稳定(OR=1.167;95% CI=1.025-1.328,p=0.020),表明 In-SII 评分每增加一个单位,患类风湿性关节炎的风险就会增加 17%。
Table 3 表 3
Weighted multivariate logistic analysis systemic immune-inflammation index and rheumatoid arthritis
加权多变量逻辑分析系统免疫炎症指数与类风湿性关节炎
Crude model | Model 1 | Model 2 | Model 3 | |||||
---|---|---|---|---|---|---|---|---|
OR 95% CI | P-value | OR 95% CI | P-value | OR 95% CI | P-value | OR 95% CI | P-value | |
SII | 1.296 (1.166, 1.441) | <0.001 | 1.291 (1.164, 1.433) | <0.001 | 1.192 (1.066, 1.332) | 0.002 | 1.167 (1.025, 1.328) | 0.020 |
Stratified by SII quartiles 按 SII 四分位数分层 | ||||||||
Q1 | ref | ref | ref | ref | ||||
Q2 | 0.948 (0.818, 1.098) | 0.474 | 1.003 (0.857, 1.173) | 0.973 | 0.980 (0.826, 1.162) | 0.811 | 0.975 (0.806, 1.181) | 0.796 |
Q3 | 0.933 (0.789, 1.102) | 0.411 | 0.991 (0.832, 1.180) | 0.915 | 0.940 (0.787, 1.124) | 0.498 | 0.906 (0.745, 1.102) | 0.320 |
Q4 | 1.310 (1.128, 1.521) | <0.001 | 1.323 (1.127, 1.554) | <0.001 | 1.200 (1.013, 1.421) | 0.035 | 1.138 (0.933, 1.388) | 0.201 |
P for trend | <0.001 | <0.001 | 0.038 | 0.254 |
We further transformed the SII from a continuous variable into a categorical variable (quartiles) for sensitivity analysis (Table (Table3).3). Compared with the lowest quartile, the risk of developing rheumatoid arthritis in the highest quartile increased by 31% (OR=1.310; 95% CI=1.128–1.521, p<0.001) in the crude model, 32% (OR=1.323; 95% CI=1.127–1.554, p<0.001) in the model 1 and 20% (OR=1.200; 95% CI=1.013–1.421, p=0.035).
我们进一步将 SII 从连续变量转化为分类变量(四分位数),以进行敏感性分析(表 3)。与最低四分位数相比,最高四分位数患类风湿性关节炎的风险在粗模型中增加了31%(OR=1.310;95% CI=1.128-1.521,p<0.001),在模型1中增加了32%(OR=1.323;95% CI=1.127-1.554,p<0.001),在模型2中增加了20%(OR=1.200;95% CI=1.013-1.421,p=0.035)。
The non-linear relationship between RA and SII
RA 与 SII 之间的非线性关系
Using restricted cubic splines, a non-linear relationship between ln-SII and RA risk was found in the original model (Fig. (Fig.2C)2C) and after adjustment for multiple covariates (Fig. (Fig.2D)2D) (p<0.001). Moreover, A threshold effect can be observed, with an inflection point at the ln-SII value of 6.36 (SII = 578.25). when the SII value is less than the cutoff value, the risk of rheumatoid arthritis is almost unchanged or even decreased, and when the SII value exceeds the cutoff value, the risk increases rapidly.
使用限制性三次样条,发现在原始模型(图(Fig.2C)2C)和调整多个协变量(图(Fig.2D)2D)后,ln-SII与RA风险之间存在非线性关系(p<0.001)。此外,还可以观察到阈值效应,在 ln-SII 值为 6.36(SII = 578.25)时出现拐点。当 SII 值小于临界值时,类风湿性关节炎的风险几乎不变甚至降低,而当 SII 值超过临界值时,风险迅速增加。
The subgroup analysis and interaction test
分组分析和交互检验
We found that the risk of rheumatoid arthritis was not consistently associated with increased SII levels (Table (Table4)4) in some subgroups. Overall, for PIR (>3.5), participants with diabetes, alcohol use (moderate) and smoking, this correlation was not statistically significant (P>0.05).
我们发现,在某些亚组中,类风湿性关节炎的发病风险与 SII 水平升高的关系并不一致(表 4)4。总体而言,就 PIR(>3.5)、患有糖尿病、饮酒(中度)和吸烟的参与者而言,这种相关性在统计学上并不显著(P>0.05)。
Table 4 表 4
Subgroup analysis for the association between SII and arthritis
SII 与关节炎关系的分组分析
Character | OR 95% CI | P-value | P for interaction 互动 P |
---|---|---|---|
Age | 0.795 | ||
Below 60 | 1.253 (1.062, 1.479) | 0.008 | |
Over 60 | 1.355 (1.196, 1.535) | <0.0001 | |
PIR | 0.318 | ||
Below 1.3 | 1.200 (1.012, 1.422) | 0.036 | |
1.3–3.5 | 1.402 (1.191, 1.651) | <0.0001 | |
Over 3.5 | 1.173 (0.929, 1.482) | 0.178 | |
BMI | 0.25 | ||
Below 25 | 1.392 (1.118, 1.732) | 0.003 | |
25–30 | 1.324 (1.059, 1.655) | 0.014 | |
Over 30 | 1.172 (1.011, 1.358) | 0.035 | |
Gender | 0.051 | ||
Male | 1.428 (1.203, 1.695) | <0.0001 | |
Female | 1.173 (1.011, 1.361) | 0.035 | |
Hypertension | 0.645 | ||
No | 1.177 (0.972, 1.425) | 0.095 | |
Yes | 1.272 (1.121, 1.443) | <0.001 | |
Diabetes | 0.08 | ||
No | 1.320 (1.144, 1.524) | <0.001 | |
Pre-diabetes | 1.513 (1.092, 2.096) | 0.013 | |
Diabetes | 1.091 (0.905, 1.314) | 0.359 | |
Hyperlipidemia | 0.111 | ||
No | 1.583 (1.221, 2.053) | <0.001 | |
Yes | 1.230 (1.092, 1.385) | <0.001 | |
Work activity 工作活动 | 0.497 | ||
No | 1.361 (1.162, 1.593) | <0.001 | |
Yes | 1.263 (1.082, 1.475) | 0.003 | |
Alcohol use | 0.405 | ||
Never | 1.581 (1.229, 2.035) | <0.001 | |
Former | 1.266 (1.072, 1.496) | 0.006 | |
Mild | 1.250 (1.007, 1.552) | 0.044 | |
Moderate | 1.140 (0.851, 1.528) | 0.377 | |
Heavy | 1.409 (1.016, 1.954) | 0.040 | |
Smoke | 0.643 | ||
Never | 1.342 (1.118, 1.611) | 0.002 | |
Former | 1.408 (1.150, 1.724) | 0.001 | |
Now | 1.171 (0.964, 1.422) | 0.112 |
Furthermore, the interaction test showed that gender, age, BMI, PIR, hypertension, diabetes, hyperlipidemia, smoking, alcohol use, and work activity had no significant effect on this connection (Table (Table4,4, interaction all P>0.05).
此外,交互作用检验表明,性别、年龄、体重指数、PIR、高血压、糖尿病、高脂血症、吸烟、饮酒和工作活动对这种联系没有显著影响(表 4,4,交互作用均 P>0.05)。
Discussion 讨论
This study finally included 37,604 participants from the NHANES 1999–2018 cohort for analysis, including 19,523 males and 18,081 females. Of these, 2642 patients had rheumatoid arthritis. Compared with normal people, patients with RA have higher levels of SII. Moreover, after adjusting for all covariates, we found that the relationship was non-linear. Further, we found that when SII is higher than 578.25, the risk of rheumatoid arthritis will increase significantly. And there were stratification effects in the PIR of more than 3.5, diabetes, alcohol moderate use, and smoking population.
这项研究最终纳入了 NHANES 1999-2018 年队列中的 37604 名参与者进行分析,包括 19523 名男性和 18081 名女性。其中,2642 名患者患有类风湿性关节炎。与正常人相比,类风湿关节炎患者的 SII 水平更高。此外,在对所有协变量进行调整后,我们发现这种关系是非线性的。此外,我们还发现,当 SII 超过 578.25 时,类风湿关节炎的风险将显著增加。在 PIR 超过 3.5、糖尿病、适度饮酒和吸烟人群中存在分层效应。
To the best of our knowledge, our study is the first to report that the SII level of patients with RA was higher than that of healthy controls by using the NHANES database. Our results are consistent with previous research. Choe et al [24] suggested that the SII scores may be useful markers that adequately reflect the activity of the RA and may lead to more accurate diagnoses. Satis et al. [21] found that the systemic immune-inflammation index could be used as a new tool, showing the RA disease activity, and through the ROC curve, they concluded that 574.20 is the best cut-off point for active RA. Their study found that the cutoff values are roughly similar to those in our study. This shows that this point has certain clinical value. However, that study also has certain limitations. For example, the study was a case-control study with a low sample size.
据我们所知,我们的研究是首次利用 NHANES 数据库报告 RA 患者的 SII 水平高于健康对照组。我们的研究结果与之前的研究结果一致。Choe 等人[ 24] 认为,SⅡ评分可能是充分反映 RA 活动性的有用标记,并可能导致更准确的诊断。Satis 等人[ 21] 发现,全身免疫炎症指数可作为一种新的工具,显示 RA 疾病的活动性,通过 ROC 曲线,他们认为 574.20 是活动性 RA 的最佳临界点。他们的研究发现,该临界值与我们的研究大致相似。这说明该分界点具有一定的临床价值。不过,该研究也有一定的局限性。例如,该研究是一项病例对照研究,样本量较少。
Compared with previous studies, our conclusions are more convincing and provide sufficient evidence. The study by Kelesoglu et al. [19] collected 106 psoriatic arthritis (PsA) patients and 103 age and gender-matched healthy individuals, showing that compared with patients in remission or with low disease activity, SII levels were significantly higher in PsA patients with moderate to severe disease (p<0.001). Similarly, Yorulmaz et al. [20] also demonstrated that SII might serve as an independent prognostic indicator for patients with psoriasis and psoriatic arthritis. Wu et al. [25] also confirmed that for patients with ankylosing spondylitis, SII was increased in AS. The SII may be a novel indicator for monitoring disease activity in AS.
与之前的研究相比,我们的结论更有说服力,也提供了足够的证据。Kelesoglu等人[ 19] 的研究收集了106名银屑病关节炎(PsA)患者和103名年龄与性别匹配的健康人,结果显示,与缓解期或疾病活动度低的患者相比,中重度PsA患者的SII水平明显更高(P<0.001)。同样,Yorulmaz 等人[ 20] 也证明 SII 可作为银屑病和银屑病关节炎患者的独立预后指标。Wu等人[ 25]也证实,强直性脊柱炎患者的SⅡ在强直性脊柱炎中增高。SII可能是监测强直性脊柱炎疾病活动性的一个新指标。
Overall, there are few studies about the systemic immunoinflammatory index and rheumatoid arthritis. Moreover, researchers must pay more attention to the fact that the systemic immune-inflammation index is a right-skewed non-normal distribution. Before the data analysis process, it is better to perform log transformation. The systemic immune-inflammation index (SII) measures the level of systemic inflammation in patients with RA and has been shown to be a strong predictor of disease activity, joint damage, and radiographic progression. In general, higher SII values are associated with more severe RA disease activity and a poorer prognosis.
总体而言,有关全身免疫炎症指数和类风湿性关节炎的研究很少。此外,研究人员必须更加关注系统免疫炎症指数是右斜非正态分布这一事实。在进行数据分析之前,最好先进行对数变换。全身免疫炎症指数(SII)测量 RA 患者的全身炎症水平,已被证明是疾病活动、关节损伤和影像学进展的有力预测指标。一般来说,SII 值越高,RA 疾病活动越严重,预后越差。
Rheumatoid arthritis affects about 0.5 to 1% of adults in developed countries, with about 5 to 50 new cases per 100,000 people each year [26]. The disease most commonly occurs in middle age, and the incidence rate in women is 2.5 times higher than in men [27, 28]. Rheumatoid arthritis caused 28,000 deaths in 1990 and 38,000 deaths in 2013 [29]. Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by inflammation of the joints, leading to pain, swelling, stiffness, and progressive joint damage. RA is a systemic disease that affects multiple joints and other organ systems, including the skin, eyes, lungs, and cardiovascular system [28]. RA is also associated with extra-articular manifestations such as rheumatoid nodules, anemia and fatigue. Osteoarthritis and rheumatoid arthritis are two completely different diseases. Osteoarthritis is cartilage degeneration [30]; rheumatoid arthritis is a systemic autoimmune disease.
在发达国家,类风湿性关节炎约影响 0.5%至 1%的成年人,每年每 10 万人中约有 5 至 50 例新病例[26]。该病最常见于中年,女性发病率是男性的 2.5 倍[27, 28]。类风湿性关节炎在 1990 年导致 28,000 人死亡,在 2013 年导致 38,000 人死亡[29]。类风湿性关节炎(RA)是一种慢性自身免疫性疾病,其特点是关节发炎,导致疼痛、肿胀、僵硬和进行性关节损伤。RA 是一种全身性疾病,影响多个关节和其他器官系统,包括皮肤、眼睛、肺部和心血管系统[28]。RA 还伴有类风湿结节、贫血和疲劳等关节外表现。骨关节炎和类风湿性关节炎是两种完全不同的疾病。骨关节炎是软骨退化[30];类风湿性关节炎是一种全身性自身免疫疾病。
The exact cause of rheumatoid arthritis (RA) is unknown, but it is believed to be a complex interaction of genetic, environmental, and immunologic factors. There is evidence of genetic predisposition to the development of RA, with certain HLA alleles being associated with increased susceptibility. Environmental factors, such as infections, trauma, and smoking, have also been implicated in the etiology of RA [4]. The immune system of RA patients is characterized by systemic inflammation and autoantibody production, leading to the activation of immune cells and the release that contribute to joint damage and functional impairment [31]. While the exact cause of RA remains unclear, a better understanding of the underlying mechanisms may lead to the development of new and effective therapies for this debilitating disease.
类风湿性关节炎(RA)的确切病因尚不清楚,但据信是遗传、环境和免疫因素的复杂相互作用。有证据表明,遗传易导致 RA 的发生,某些 HLA 等位基因与 RA 的易感性增加有关。感染、创伤和吸烟等环境因素也与 RA 的病因有关[ 4]。RA 患者免疫系统的特点是全身炎症和自身抗体的产生,导致免疫细胞的激活和释放,从而造成关节损伤和功能障碍[31]。虽然 RA 的确切病因仍不清楚,但更好地了解其潜在机制可能有助于开发治疗这种使人衰弱的疾病的有效新疗法。
The systemic immune-inflammation index (SII) is an indicator used to assess the degree of systemic inflammation in an individual. It is calculated by the platelet count, neutrophil count, and lymphocyte count (PLT×N/L ratio) [11]. Overall, some researchers found that this indicator could be used to predict mortality in cancer patients. Other researchers think it can be used as an indicator of the progression of a certain disease. The study by Li et al. [13] suggested that high SII levels may increase overall mortality and cardiovascular disease mortality in the general population, using NHANES follow-up data from 1999 to 2014. He et al. [12] showed a correlation between SII and all-cause mortality in the US arteriosclerotic cardiovascular disease (ASCVD) population. Increased SII was associated with poor survival in ASCVD patients. Guo et al. [32] found that SII levels in T2DM patients were associated with the development of diabetic kidney disease (DKD). SII may be a cost-effective and simple method to detect DKD. Zhang et al. [33] have shown that elevated levels of SII may be a potential risk factor for the development of osteoporosis in post-menopausal women. A similar conclusion was reached by Tang et al. [17].
全身免疫炎症指数(SII)是用于评估个体全身炎症程度的指标。它由血小板计数、中性粒细胞计数和淋巴细胞计数(PLT×N/L 比值)计算得出[11]。总体而言,一些研究人员发现该指标可用于预测癌症患者的死亡率。另一些研究人员则认为它可用作某种疾病进展的指标。Li等人的研究[ 13]利用1999年至2014年的NHANES随访数据表明,高SII水平可能会增加普通人群的总死亡率和心血管疾病死亡率。He 等人[ 12] 的研究表明,在美国动脉硬化性心血管疾病(ASCVD)人群中,SII 与全因死亡率之间存在相关性。SII 增加与 ASCVD 患者生存率低有关。Guo 等人[ 32] 发现,T2DM 患者的 SII 水平与糖尿病肾病(DKD)的发生有关。SII 可能是检测 DKD 的一种经济而简单的方法。Zhang 等人[ 33] 的研究表明,SⅡ水平升高可能是绝经后妇女发生骨质疏松症的潜在危险因素。Tang 等人也得出了类似的结论[ 17]。
Our research has some advantages. This is the first study to explore the relationship between the systemic immune-inflammation index and osteoarthritis based on the large sample size of the NHANES database. Furthermore, we use a weighted logistic regression model for analysis since the NHANES database is composed of multi-stage complex sampling data, and we have adjusted other covariates, which makes the conclusions drawn in this study more accurate and reliable. Additionally, we ln-transformed the SII before the analysis process to ensure it had a normal distribution. Finally, we used restrictive cubic spline and smooth curve fitting to explore their non-linear relationship and further calculated the inflection points.
我们的研究具有一些优势。这是第一项基于 NHANES 数据库的大样本量来探讨全身免疫炎症指数与骨关节炎之间关系的研究。此外,由于 NHANES 数据库由多阶段复杂抽样数据组成,我们采用了加权逻辑回归模型进行分析,并对其他协变量进行了调整,这使得本研究得出的结论更加准确可靠。此外,我们在分析前对 SII 进行了 ln 变换,以确保其呈正态分布。最后,我们使用限制性三次样条曲线和平滑曲线拟合来探索它们之间的非线性关系,并进一步计算拐点。
However, our study also has some limitations. First, some variables in this study come from questionnaires and self-reports, which are prone to bias. Furthermore, since NHANES did not record some classic inflammatory factors (such as TNF-α, interleukin-6, interleukin-10, etc.), relevant indicators cannot be included to obtain more comprehensive results. More researchers should continue to explore the inflammatory markers in rheumatoid arthritis. We hope this study provides a scientific data reference for future research. We will also include more classical inflammatory factors in future studies to explore the relationship between osteoarthritis and systemic immune-inflammatory indices.
不过,我们的研究也有一些局限性。首先,本研究中的一些变量来自问卷调查和自我报告,容易产生偏差。此外,由于NHANES并没有记录一些经典的炎症因子(如TNF-α、白细胞介素-6、白细胞介素-10等),因此无法纳入相关指标以获得更全面的结果。更多的研究者应继续探索类风湿关节炎的炎症指标。我们希望这项研究能为今后的研究提供科学的数据参考。在今后的研究中,我们还将纳入更多的经典炎症因子,探讨骨关节炎与全身免疫炎症指标之间的关系。
Conclusion 结论
In summary, our study provides new insights into the relationship between rheumatoid arthritis and SII. In general, there is a positive correlation between SII and rheumatoid arthritis. The SII cut-off (578.25) has a certain clinical application value. Our study shows that SII is a novel, valuable, and convenient inflammatory marker that can be used to predict the risk of rheumatoid arthritis in adults. Low cost and easy to collect and calculate are the advantages of SII. We hope that the SII will become a good evaluation index for predicting cancer prognosis and evaluating disease activity.
总之,我们的研究为类风湿关节炎与 SII 之间的关系提供了新的见解。总的来说,SII 与类风湿性关节炎之间存在正相关。SII 临界值(578.25)具有一定的临床应用价值。我们的研究表明,SII 是一种新颖、有价值且方便的炎症标志物,可用于预测成人类风湿性关节炎的风险。成本低、易于采集和计算是 SII 的优点。我们希望 SII 能成为预测癌症预后和评估疾病活动性的良好评价指标。
Acknowledgements 致谢
The authors thank all the participants and staff of the National Health and Nutrition Examination Survey and the National Center for Environmental Health for their valuable contributions.
作者感谢全国健康与营养调查(National Health and Nutrition Examination Survey)和全国环境健康中心(National Center for Environmental Health)的所有参与者和工作人员做出的宝贵贡献。
Abbreviations 缩略语
SII | Systemic immune-inflammation index 全身免疫炎症指数 |
RA | Rheumatoid arthritis 类风湿性关节炎 |
OA | Osteoarthritis |
PA | Psoriatic arthritis 银屑病关节炎 |
AS | Ankylosing spondylitis 强直性脊柱炎 |
NHANES | National Health and Nutrition Examination Survey 全国健康与营养调查 |
BMI | Body mass index 体重指数 |
CI | Confidence interval 置信区间 |
Authors’ contributions 作者的贡献
BL performed the data analysis and wrote the manuscript. JW, YY L and KP L contributed to data collection and the literature search. Q Zh oversighted and managed responsibility for the research activity. All authors contributed to the design of the study protocol and reviewed the manuscript. The author(s) read and approved the final manuscript.
BL 进行了数据分析并撰写了手稿。JW、YY L和KP L参与了数据收集和文献检索。Q Zh 负责监督和管理研究活动。所有作者都参与了研究方案的设计并审阅了手稿。作者阅读并批准了最终手稿。
Availability of data and materials
数据和材料的可用性
Publicly available datasets were analyzed in this study. This data can be found here: The National Health and Nutrition Examination Survey dataset at https://www.cdc.gov/nchs/nhanes/index.htm
本研究分析了可公开获得的数据集。这些数据可在此处找到:全国健康与营养调查数据集,网址:https://www.cdc.gov/nchs/nhanes/index.htm
Declarations 声明
伦理批准和参与同意书
The ethics committee approved the study of Beijing Ditan Hospital, Capital Medical University. The ethics committee waived the requirement for informed consent from all patients.
首都医科大学附属北京地坛医院伦理委员会批准了本研究。伦理委员会免除了所有患者知情同意的要求。
The authors declare no competing interests.
作者声明不存在利益冲突。
Footnotes 脚注
Publisher’s Note 出版商说明
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Contributor Information 投稿人信息
Bo Liu, Email: moc.361@obuiltdys.
Bo Liu,电子邮件:moc.361@obuiltdys.
Qiang Zhang, Email: moc.361@212202gnaiqgnahz.
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这里提供的文章来自《关节炎研究与治疗》(Arthritis Research & Therapy),由 BMC 提供。