中性粒细胞与淋巴细胞亚群比值在非小细胞肺癌临床分期及病理分型中的应用价值研究

Application value of neutrophil to lymphocyte subsets ratios in clinical staging andpathological typing of non-small cell lung cancer

目的探讨中性粒细胞与淋巴细胞亚群比值在非小细胞肺癌(NSCLC)临床分期及病理分型中的应用价值。方法选取2018年1月至2020年12月在该院住院治疗的经组织病理学确诊的NSCLC患者132例作为NSCLC组。另选取同期在该院体检的健康者85例作为对照组,检测并计算两组研究对象的中性粒细胞与淋巴细胞亚群比值,并进行比较。结果与对照组比较,NSCLC组CD3^(+)T细胞、CD4^(+)T细胞、CD8^(+)T细胞、B细胞、自然杀伤(NK)细胞、CD4^(+)/CD8^(+)明显降低,中性粒细胞与淋巴细胞比值(NLR)、中性粒细胞与CD3^(+)T细胞比值(N/CD3^(+))、中性粒细胞与CD4^(+)T细胞比值(N/CD4^(+))、中性粒细胞与CD8^(+)T细胞比值(N/CD8^(+))、中性粒细胞与B细胞比值(N/B)、中性粒细胞与NK细胞比值(N/NK)明显升高(P<0.05)。与腺癌组相比,鳞癌组NLR、N/CD3^(+)、N/CD4^(+)、N/B、N/NK明显增高(P<0.05)。Ⅰ期组、Ⅱ期组、Ⅲ期组、Ⅳ期组NLR、N/CD3^(+)、N/CD4^(+)、N/CD8^(+)、N/B、N/NK均显著高于对照组(P<0.05),与Ⅰ期组相比,Ⅲ期组和Ⅳ期组N/CD3^(+)、N/CD4^(+)、N/CD8^(+)、N/B均显著增高(P<0.05),CD3^(+)T细胞、B细胞明显降低(P<0.05)。受试者工作特征曲线分析显示,中性粒细胞和淋巴细胞亚群比值的曲线下面积和约登指数分别较相应的淋巴细胞亚群高。基于机器学习的线性支持向量分类器(Linear SVC)算法,将N/CD3^(+)、N/CD4^(+)、N/CD8^(+)、N/B、N/NK指标用于构建NSCLC风险预测模型,结果显示,其曲线下面积可达到0.929,阳性预测值为0.911,阴性预测值为0.787。结论中性粒细胞与淋巴细胞亚群比值与NSCLC的临床分期及病理分型关系密切,N/CD3^(+)、N/CD4^(+)、N/CD8^(+)、N/B、N/NK联合检测的临床诊断效能较高,可以为NSCLC的早期诊断和病情严重程度的评估提供新的诊疗思路。

Objective To explore the application value of neutrophil to lymphocyte subsets ratios in clinical staging and pathological classification of non-small cell lung cancer(NSCLC).Methods A total of 132 NSCLC patients who were hospitalized and diagnosed by histopathology from January 2018 to December 2020 in the hospital were selected as the NSCLC group.Another 85 healthy individuals who underwent physical examinations at the same hospital were selected as the control group,and the neutrophil to lymphocyte subsets ratios of the two study groups were detected and calculated for comparison.Results Compared with the control group,the CD3^(+)T cell,CD4^(+)T cell,CD8^(+)T cell,B cell,natural killer(NK)cell,and CD4^(+)/CD8^(+)in the NSCLC group were significantly reduced,while neutrophil to lymphocyte ratio(NLR),neutrophil to CD3^(+)T cell ratio(N/CD3^(+)),neutrophil to CD4^(+)T cell ratio(N/CD4^(+)),neutrophil to CD8^(+)T cell ratio(N/CD8^(+)),neutrophil to B cell ratio(N/B),and neutrophil to NK cell ratio(N/NK)significantly increased(P<0.05).Compared with adenocarcinoma group,NLR,N/CD3^(+),N/CD4^(+),N/B,and N/NK were higher in the squamous cell carcinoma group(P<0.05).NLR,N/CD3^(+),N/CD4^(+),N/CD8^(+),N/B and N/NK in the stageⅠgroup,the stageⅡgroup,the stageⅢgroup and the stageⅣgroup were significantly higher than those in the control group(P<0.05).Compared with the stageⅠgroup,N/CD3^(+),N/CD4^(+),N/CD8^(+),and N/B in the stageⅢgroup and the stageⅣgroup were significantly increased(P<0.05),while CD3^(+)T cell and B cell were significantly decreased(P<0.05).Receiver operating characteristic curve results showed that the area under the curve and Youden index of the neutrophils to lymphocyte subsets ratios were higher than those of the corresponding lymphocyte subsets.The Linear Support Vector Classification(Linear SVC)algorithm based on machine learning was used to construct a NSCLC risk prediction model using N/CD3^(+),N/CD4^(+),N/CD8^(+),N/B,and N/NK indicators.The results showed that the area under the curve could reach 0.929,with a positive predictive value of 0.911 and a negative predictive value of 0.787.Conclusion The neutrophil to lymphocyte subsets ratios are closely related to the clinical staging and pathological classification of NSCLC.The combined detection of N/CD3^(+),N/CD4^(+),N/CD8^(+),N/B,and N/NK has high clinical diagnostic efficacy and could provide new diagnostic and therapeutic ideas for the early diagnosis and assessment of the severity of NSCLC.