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文章:

结合经典与新型中性粒细胞相关生物标志物识别非小细胞肺癌

Combining Classic and Novel Neutrophil-Related Biomarkers to Identify Non-Small-Cell Lung Cancer

原文发布日期:25 January 2024

DOI: 10.3390/cancers16030513

类型: Article

开放获取: 是

 

英文摘要:

Background: Recent studies have revealed that neutrophils play a crucial role in cancer progression. This study aimed to explore the diagnostic value of neutrophil-related biomarkers for non-small-cell lung cancer (NSCLC). Methods: We initially assessed the associations between classic neutrophil-related biomarkers (neutrophil-to-lymphocyte ratio (NLR), absolute neutrophil counts (NEU), absolute lymphocyte counts (LYM)) and NSCLC in 3942 cases and 6791 controls. Then, we measured 11 novel neutrophil-related biomarkers via Luminex Assays in 132 cases and 66 controls, individually matching on sex and age (±5 years), and evaluated their associations with NSCLC risk. We also developed the predictive models by sequentially adding variables of interest and assessed model improvement. Results: Interleukin-6 (IL-6) (odds ratio (OR) = 10.687, 95% confidence interval (CI): 3.875, 29.473) and Interleukin 1 Receptor Antagonist (IL-1RA) (OR = 8.113, 95% CI: 3.182, 20.689) shows strong associations with NSCLC risk after adjusting for body mass index, smoking status, NLR, and carcinoembryonic antigen. Adding the two identified biomarkers to the predictive model significantly elevated the model performance from an area under the receiver operating characteristic curve of 0.716 to 0.851 with a net reclassification improvement of 97.73%. Conclusions: IL-6 and IL-1RA were recognized as independent risk factors for NSCLC, improving the predictive performance of the model in identifying disease.

 

摘要翻译: 

背景:近期研究表明,中性粒细胞在癌症进展中发挥关键作用。本研究旨在探讨中性粒细胞相关生物标志物对非小细胞肺癌(NSCLC)的诊断价值。方法:我们首先在3942例病例和6791例对照中评估了经典中性粒细胞相关生物标志物(中性粒细胞与淋巴细胞比值(NLR)、中性粒细胞绝对计数(NEU)、淋巴细胞绝对计数(LYM))与NSCLC的关联性。随后,我们通过Luminex检测技术对132例病例和66例对照(按性别和年龄(±5岁)进行个体匹配)测量了11种新型中性粒细胞相关生物标志物,并评估其与NSCLC风险的关联。通过逐步纳入相关变量构建预测模型,并评估模型改进效果。结果:在校正体重指数、吸烟状况、NLR和癌胚抗原后,白细胞介素-6(IL-6)(比值比(OR)= 10.687,95%置信区间(CI):3.875-29.473)和白细胞介素-1受体拮抗剂(IL-1RA)(OR = 8.113,95% CI:3.182-20.689)与NSCLC风险呈现显著关联。将这两种标志物纳入预测模型后,受试者工作特征曲线下面积从0.716显著提升至0.851,净重分类改善率达97.73%。结论:IL-6和IL-1RA被确认为NSCLC的独立危险因素,可显著提升疾病识别预测模型的性能。

 

原文链接:

Combining Classic and Novel Neutrophil-Related Biomarkers to Identify Non-Small-Cell Lung Cancer

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