外周血绝对嗜酸性粒细胞计数水平对肺癌预后的评估价值研究  

Evaluation Value of Peripheral Absolute Eosinophil Count for the Prognosis of Lung Cancer

作　　者：易芬 王勇[1] 徐爱晖[1] YI Fen;WANG Yong;XU Aihui(Department of Respiratory and Critical Care Medicine,the First Affiliated Hospital of Anhui Medical University,Hefei 230022,China)

机构地区：[1]安徽医科大学第一附属医院呼吸与危重症医学科,安徽省合肥市230022

出　　处：《中国全科医学》2024年第32期4001-4008,共8页Chinese General Practice

基　　金：紧急医学救援状态下灾区医疗服务保障和重点传染病防治的规范与关键技术应用性研究(201302003)。

摘　　要：背景世界范围内肺癌的发生率和死亡率均较高且呈升高趋势,目前针对肺癌的发生、发展及预后已有许多研究,但仍缺乏早期评估肺癌预后的简便、有效手段。目的探讨绝对嗜酸性粒细胞计数水平对肺癌患者的预后评估的意义。方法回顾性分析2019年6月—2022年12月于安徽医科大学第一附属医院住院的152例肺癌患者的临床资料,通过门诊及电话随访的方式对患者进行随访调查,评估患者是否出现疾病进展,随访至2023年5月。将出现肿瘤复发、转移或死亡的患者纳入预后欠佳组,余纳入预后良好组,并记录患者无进展生存期(PFS)。通过组间差异性比较筛选影响肺癌患者预后的影响因素并进行多因素Cox回归分析;采用Kaplan-Meier生存分析探讨绝对嗜酸性粒细胞计数对肺癌患者预后的影响,绘制绝对嗜酸性粒细胞计数评估肺癌预后的受试者工作特征(ROC)曲线,计算ROC曲线下面积(AUC)并比较其预测价值;从全基因组关联分析汇总数据和国际肺癌研究联盟分别收集绝对嗜酸性粒细胞计数和肺癌的相关数据集进行孟德尔随机化分析,评估绝对嗜酸性粒细胞计数与肺癌之间的因果关系。结果按照肺癌患者预后情况分为预后良好组(n=72)和预后欠佳组(n=80),两组患者绝对嗜酸性粒细胞计数水平比较,差异有统计学意义(P=0.004)。多因素Cox回归分析结果显示,绝对嗜酸性粒细胞计数是肺癌生存结局的独立影响因素(HR=1.58,95%CI=1.03~2.44,P=0.037)。Kaplan-Meier生存分析结果显示,绝对嗜酸性粒细胞计数升高组(n=76)的平均PFS[(618.44±72.57)d]短于正常组(n=76)的平均PFS[(842.32±76.04)d](P=0.048)。绝对嗜酸性粒细胞计数预测肺癌预后的AUC为0.634。孟德尔随机化分析结果得出绝对嗜酸性粒细胞计数可能是东亚人群中肺癌的总体风险因素,且为不利因素(OR=1.07,95%CI=1.01~1.13,P=0.030)。结论绝对嗜酸性粒细胞计数水平的Background Lung cancer remains a significant global health challenge,with both its incidence and mortality rates on the rise worldwide.Despite numerous investigations into its etiology,progression,and prognostic indicators,a pressing need persists for straightforward and efficient methods to assess the early prognosis of lung cancer.Objective This study aims to investigate the prognostic significance of absolute eosinophil count level in patients with lung cancer.Methods We conducted a retrospective analysis of clinical data from 152 lung cancer patients admitted to the First Affiliated Hospital of Anhui Medical University between June 2019 and December 2022,with follow-up conducted until May 2023.Patients experiencing tumor recurrence,metastasis,or mortality were categorized into the poor prognosis group,while the remaining patients comprised the good prognosis group.Progression-free survival time(PFS)was meticulously recorded.Group comparisons were made to identify factors influencing lung cancer prognosis,followed by multivariate Cox regression analysis.Additionally,Kaplan-Meier survival analysis was employed to assess the impact of absolute eosinophil count on survival.Receiver operating characteristic(ROC)curve analysis was utilized to evaluate the prognostic efficacy of lung cancer,with the area under the ROC curve(AUC)calculated to gauge its predictive value.To further explore the relationship between eosinophil counts and lung cancer,datasets were procured from genome-wide association analysis pooled data and the International Consortium for Lung Cancer Research for Mendelian randomization analysis,elucidating potential causal links.Results Patients were stratified into good and poor prognosis groups based on their lung cancer prognosis.A statistically significant contrast in absolute eosinophil count was observed between these groups(P=0.004).Multivariate Cox regression analysis highlighted absolute eosinophil count as an independent risk factor for lung cancer survival outcomes(HR=1.58,95%CI=1.03-2.44,P

关 键 词：肺癌 绝对嗜酸性粒细胞计数 预后 COX回归分析 孟德尔随机化分析 

分 类 号：R734.2[医药卫生—肿瘤]