Sun Li, Wu Yanling, Akinyemi Lydia Idowu, Cao Zhiqiu, Fan Zhanhong, Liu Huahua, Yang Ziyi, Zhang Leilei, Zhang Feng
School of Nursing and Rehabilitation, Nantong University, Nantong, Jiangsu, China.
Nantong Maternal and Child Health Care Hospital, Nantong, Jiangsu, China.
Cancer Med. 2025 Mar;14(6):e70777. doi: 10.1002/cam4.70777.
To investigate the association between the systemic immunity-inflammation index (SII) and fatigue, cancer, and cancer-related fatigue (CRF) populations.
The National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018 provided data for this retrospective cross-sectional study. By dividing the platelet count by the neutrophil count and the lymphocyte count, SII was calculated. Participants were categorized into four groups: normal, fatigue, cancer, and cancer-related fatigue (CRF), with the normal group serving as the reference. Binary logistic regression was applied to assess the correlations. The dose-response relationship between SII and outcomes in the four groups was evaluated using restricted cubic splines. Use threshold effect analysis to determine the optimal SII value for each of the three groups. Stratified and subgroup analyses were performed based on sociodemographic factors and confounders, with specific attention to fatigue severity levels (mild, moderate, severe) in the fatigue and CRF groups.
Data analysis included a total of 32,491 participants, including 14,846 in the normal group, 14,581 in the fatigue group, 1520 in the cancer group, and 1544 in the CRF group. The results of binary logistic regression showed that SII was positively correlated with the fatigue group (1.43[1.33, 1.55]), cancer group (1.67 [1.43, 1.95]) and CRF group (1.93 [1.66, 2.25]). Restricted cubic spline analysis revealed a linear relationship between SII and outcomes. The threshold values (k) for each of these groups were identified as 464.78 × 10 cells/μL, 448.97 × 10 cells/μL, and 454.65 × 10 cells/μL, respectively. Stratified analysis indicates that most groups exhibit significant differences. The subgroup analysis indicated that fatigue severity increased with higher SII levels, with the CRF group exhibiting the highest rate of severe fatigue (171% increase).
SII is positively correlated with fatigue, cancer, and CRF in a linear way. Higher SII values are associated with greater fatigue, particularly in the CRF population.
探讨全身免疫炎症指数(SII)与疲劳、癌症及癌症相关疲劳(CRF)人群之间的关联。
2005年至2018年的美国国家健康与营养检查调查(NHANES)为这项回顾性横断面研究提供了数据。通过将血小板计数除以中性粒细胞计数和淋巴细胞计数来计算SII。参与者被分为四组:正常组、疲劳组、癌症组和癌症相关疲劳组(CRF),以正常组作为参照。采用二元逻辑回归评估相关性。使用受限立方样条评估四组中SII与结局之间的剂量反应关系。使用阈值效应分析确定三组各自的最佳SII值。根据社会人口统计学因素和混杂因素进行分层和亚组分析,特别关注疲劳组和CRF组的疲劳严重程度水平(轻度、中度、重度)。
数据分析共纳入32491名参与者,其中正常组14846人,疲劳组14581人,癌症组1520人,CRF组1544人。二元逻辑回归结果显示,SII与疲劳组(1.43[1.33, 1.55])、癌症组(1.67 [1.43, 1.95])和CRF组(1.93 [1.66, 2.25])呈正相关。受限立方样条分析揭示了SII与结局之间的线性关系。这些组各自的阈值(k)分别确定为464.78×10⁹细胞/μL、448.97×10⁹细胞/μL和454.65×10⁹细胞/μL。分层分析表明大多数组存在显著差异。亚组分析表明,随着SII水平升高,疲劳严重程度增加,CRF组的严重疲劳发生率最高(增加171%)。
SII与疲劳、癌症和CRF呈线性正相关。较高的SII值与更严重的疲劳相关,尤其是在CRF人群中。