摘要
目的探讨非小细胞肺癌(NSCLC)患者外周血簇分化抗原64(CD64)指数、白介素-6(IL-6)水平与术后感染的关系及其联合预测术后肺部感染的价值。方法前瞻性选取2021年5月至2024年5月河南省人民医院收治的350例NSCLC患者纳入研究。统计术后住院期间所有患者肺部感染发生情况,350例NSCLC患者研究期间脱落9例,341例完成研究,将341例患者根据是否发生肺部感染分为感染组(n=61)和未感染组(n=280)。比较两组患者的围术期一般资料、手术前后外周血CD64指数、IL-6水平,应用Logistic回归分析NSCLC患者术后肺部感染的影响因素,应用受试者工作特征(ROC)曲线分析外周血CD64指数、IL-6预测NSCLC患者术后肺部感染的价值。将常规影响因素联合作为常规模型,常规模型联合外周血CD64指数、IL-6作为新模型,应用曲线下面积(AUC)、净重新分类指数(NRI)和综合判别改善指数(IDI)评价两种模型预测NSCLC患者术后肺部感染的价值。结果感染组患者的年龄、糖尿病占比、COPD占比、临床分期Ⅲ期占比、手术时间、机械通气时间≥6 h占比分别为(65.47±7.21)岁、55.74%、45.90%、47.54%、(3.08±0.75)h、52.46%,明显高于未感染组的(59.63±6.59)岁、39.29%、25.71%、32.86%、(2.31±0.64)h、32.50%,差异均有统计学意义(P<0.05);感染组患者术后第1天的外周血CD64指数、IL-6水平分别为4.06±1.29、(310.75±72.68)pg/mL,明显高于未感染组的2.18±0.65、(229.63±56.14)pg/mL,差异均有统计学意义(P<0.05);Logistic回归分析结果显示,年龄、COPD、手术时间、机械通气时间、术后第1天外周血CD64指数、IL-6水平均是NSCLC患者术后肺部感染的影响因素(P<0.05);术后第1天外周血CD64指数、IL-6预测NSCLC患者术后肺部感染的AUC分别为0.723、0.720;常规模型预测NSCLC患者术后肺部感染的AUC为0.824,新模型的AUC为0.921,新模型的AUC明显大于常规模型的AUC(P<0.05),且新模型与常规模型比较,NRI、IDI均>0(P<0.05)。结论NSCLC患者术后第1天外周血CD64指数、IL-6水平升高是术后肺部感染的独立危险因素,有助于预测肺部感染发生风险,尤其是与常规影响因素联合可为临床识别肺部感染高危患者提供可靠临床依据。
Objective To investigate the association of peripheral blood cluster of differentiation 64(CD64)index and interleukin-6(IL-6)levels with postoperative infection in patients with non-small cell lung cancer(NSCLC)and to assess the predictive value of their combined application for postoperative pulmonary infection.Methods A total of 350 patients with NSCLC admitted to Henan Provincial People's Hospital from May 2021 to May 2024 were prospectively selected for inclusion in this prospective study.The incidence of pulmonary infection among all patients during postoperative hospitalization was statistically analyzed.Among the 350 NSCLC patients,nine patients dropped out,leaving 341 who completed the study.Based on whether pulmonary infection developed,341 patients were divided into an infection group(n=61)and a non-infection group(n=280).Perioperative demographic and clinical data,as well as pre-and postoperative peripheral blood CD64 index and IL-6 levels,were compared between groups.Logistic regression identified influencing factors of postoperative pulmonary infection in NSCLC patients.Receiver operating characteristic(ROC)curves was used to evaluate the value of peripheral blood CD64 index and IL-6 in predicting postoperative pulmonary infection in NSCLC patients.Conventional risk factors constituted the traditional model,while adding peripheral blood CD64 index and IL-6 formed a new model.Predictive performance was compared using area under the curve(AUC),net reclassification improvement(NRI),and integrated discrimination improvement(IDI).Results Age,diabetes proportion,chronic obstructive pulmonary disease(COPD)proportion,clinical stageⅢproportion,operation time,and proportion of mechanical ventilation time of≥6 h in the infection group were(65.47±7.21)years,55.74%,45.90%,47.54%,(3.08±0.75)h,and 52.46%,respectively,which were significantly higher than corresponding(59.63±6.59)years,39.29%,25.71%,32.86%,(2.31±0.64)h,and 32.50%in the non-infection group(all P<0.05).On postoperative day 1,the peripheral blood CD64 index and IL-6 levels in the infection group were(4.06±1.29)and(310.75±72.68)pg/mL,respectively,which were significantly higher than corresponding(2.18±0.65)and(229.63±56.14)pg/mL in the non-infection group(both P<0.05).Logistic regression analysis indicated that age,COPD,operation time,mechanical ventilation time,and postoperative day-1 CD64 index and IL-6 level were independent factors influencing postoperative pulmonary infection in NSCLC patients(all P<0.05).AUCs for postoperative day 1 CD64 index and IL-6 were 0.723 and 0.720,respectively.The conventional model had an AUC of 0.824,whereas the new model achieved an AUC of 0.921;the new model’s AUC was significantly higher(P<0.05)and yielded positive NRI and IDI values compared with the conventional model(both P<0.05).Conclusion Elevated peripheral blood CD64 index and IL-6 levels on postoperative day 1 are independent risk factors for postoperative pulmonary infection in NSCLC patients,which can help predict the risk of pulmonary infection.In particular,when combined with conventional risk factors,these biomarkers offer reliable clinical evidence for identifying high-risk patients for pulmonary infection in clinical practice.
作者
张祎苒
王萌
沈思钒
罗伟光
乔辉
郑培明
ZHANG Yi-ran;WANG Meng;SHEN Si-fan;LUO Wei-guang;QIAO Hui;ZHENG Pei-ming(Department of Clinical Laboratory,Henan Provincial People's Hospital,Zhengzhou 450000,Henan,CHINA;Department of Medical Imaging Henan Provincial People's Hospital,Zhengzhou 450000,Henan,CHINA)
出处
《海南医学》
2025年第11期1622-1627,共6页
Hainan Medical Journal
基金
2023年度河南省医学科技攻关计划联合共建项目(编号:LHGJ20230035)。
关键词
非小细胞肺癌
术后感染
簇分化抗原64
白介素-6
预测
Non-small cell lung cancer
Postoperative infection
Cluster of differentiation 64
Interleukin-6
Prediction
