Background: Inflammation within tumor microenvironments has been correlated to numerous malignancies. This study aims to explore its significance in thyroid cancer (TC). Methods: Retrospective analysis of 157 thyroid carcinomas and 40 benign cases involved initial univariate analysis. The value of neutrophils/value of lymphocytes (NLR), value of platelets/value of lymphocytes (PLR), value of lymphocytes/value of monocytes (LMR), and value of platelets × value of neutrophils/value of lymphocytes (SII) indexes were related to TC characteristics and number and location of involved lymph nodes using χ2or Fischer’s exact tests for categorical variables and Student’st-tests for continuous ones. A 1:1 propensity score matching balanced malignant and benign TC groups based on age, sex, and tumor size was used. Post-matching, a multivariate logistic model integrated sex, age, Central lymph node metastases (CLNM), and SII index. Statistically significant immune index values underwent ROC curve analysis for determining cut-offs. Among the 157 malignant TC, median test and density plots were performed. Results: The SII index emerged as a predictor of malignancy in both univariate and multivariate analyses (p-value = 0.0202). The ROC curve indicated a cut-off SII value of 465.71, (specificity = 58% [95% CI: 0.43–0.73]; sensitivity = 80% [95% CI: 0.68–0.93]). Median SII index values for tumor sizes of 1 and >1 were 522.8 and 654.8, respectively (p-value = 0.016). When central lymph nodes metastases(CLNMs) was considered (CLNM = 0 vs. CLNM > 0), median SII values were 530.7 and 1121.7, respectively (p-value = 0.011). Conclusions: The SII index appears to be a valuable tool in the presence of TC, showing correlations with malignancy, tumor size, and CLNMs.
背景：肿瘤微环境中的炎症反应与多种恶性肿瘤的发生发展相关。本研究旨在探讨其在甲状腺癌（TC）中的临床意义。方法：回顾性分析157例甲状腺癌及40例良性病例，首先进行单因素分析。采用χ²检验或Fisher精确检验处理分类变量，Student t检验处理连续变量，分析中性粒细胞/淋巴细胞比值（NLR）、血小板/淋巴细胞比值（PLR）、淋巴细胞/单核细胞比值（LMR）及系统性免疫炎症指数（SII，血小板计数×中性粒细胞计数/淋巴细胞计数）与甲状腺癌临床特征、淋巴结转移数量及部位的相关性。通过1:1倾向评分匹配法，依据年龄、性别及肿瘤大小对恶性与良性甲状腺癌组进行平衡。匹配后，构建包含性别、年龄、中央区淋巴结转移（CLNM）及SII指数的多因素逻辑回归模型。对具有统计学意义的免疫炎症指标进行受试者工作特征（ROC）曲线分析以确定最佳截断值。在157例恶性甲状腺癌中，进行中位数检验及密度分布图分析。结果：单因素及多因素分析均显示SII指数是甲状腺恶性肿瘤的预测因子（p值=0.0202）。ROC曲线确定SII最佳截断值为465.71（特异性=58% [95% CI: 0.43–0.73]；敏感性=80% [95% CI: 0.68–0.93]）。肿瘤直径≤1 cm与>1 cm组的中位SII值分别为522.8和654.8（p值=0.016）。按中央区淋巴结转移状态分组（CLNM=0 vs. CLNM>0），中位SII值分别为530.7和1121.7（p值=0.011）。结论：SII指数可作为甲状腺癌诊疗中有价值的辅助指标，其与恶性肿瘤风险、肿瘤大小及中央区淋巴结转移状态均显示出显著相关性。
Inflammation and Thyroid Cancer: Deciphering the Role of Blood Immune Indexes
肿瘤(癌症)患者之家