淋巴细胞与单核细胞比值对晚期肺癌预后预测的价值

目的:探讨淋巴细胞与单核细胞比值（LMR）对晚期肺癌预后预测的价值。方法:回顾性分析2012年12月至2014年12月初次就诊我院的晚期肺癌患者，LMR分界值由受试者工作曲线（ROC）分析确定；分析LMR表达与晚期肺癌患者临床特征的关系；采用Cox风险回归模型分析影响晚期肺癌患者总生存的预后因素。结果:根据ROC曲线，LMR最佳临界值AUC=0.581，所有研究对象分为高LMR（n=34）和低LMR（n=13）。LMR水平与病理类型、临床分期、ECOG评分有关（P<0.05）；与年龄、性别、吸烟史无关（P>0.05）。高LMR组和低LMR组的中位OS分别为28.8个月和16.2个月；中位PFS时间分别20.7个月和11.6个月，两组比较均有统计学差异（P<0.05）；Cox风险比例模型显示病理类型、吸烟史和LMR水平是影响晚期肺癌患者总生存的独立预后因素（P<0.05）。结论:LMR是晚期肺癌患者预后的独立影响因素之一，且与晚期肺癌的生存呈正比关系，对晚期肺癌患者的预后具有良好的预测价值。

Clinical research for lymphocyte and monocyte ratio on prognosis of advanced-stage lung cancer

Objective: To evaluate the value of lymphocyte and monocyte ratio(LMR) in predicting the prognosis of patients with advanced-stage lung cancer.Methods:The patients with advanced-stage lung cancer met the criterion were enrolled to this study from December 2012 to December 2014.The best diagnostic level of LMR was employed by receiver operating characteristic curve (ROC).The relationship between clinical characteristics of patients with advanced-stage lung cancer and the level of LMR was analyzed.Cox hazard-ratio model was used to analyzed the prognostic factors of advanced-stage lung cancer.Results:The best cut-off point AUA was 0.581 based on the results of ROC.All patients were divided into high LMR group（n=34）and low LMR （n=13）.The level of LMR was associated to the pathologic，clinical stage and ECOG scores（P<0.05）.The results were opposite to the age，sex and smoking historic(P>0.05）.The median overall survival was 28.8 months and 16.2 months in high LMR group and low LMR group，meanwhile，the progression-free survival in two groups was 20.7 months and 11.6 months，there were significant difference between them（P<0.05）.According to the Cox hazard-ratio model results，the pathologic，smoking historic and the level of LMR were the independent factors influencing overall survival（P<0.05）.Conclusion:LMR is one of the independent prognosis factors to the patients with advanced-stage lung cancer，the higher level of LMR，the better for survival.It is benefit to predict the prognosis of advanced-stage lung cancer.