新疆医科大学学报

目的 探究血清淀粉样蛋白A(SAA)、可溶性CD14(sCD14)及可溶性髓系细胞触发受体-1(sTREM-1)对非小细胞肺癌(NSCLC)患者胸腔镜肺切除术后肺部感染的评估价值。方法 应用回顾性分析法，纳入对象为2020年1月至2025年9月苏州市广慈肿瘤医院、苏州市立医院、盱眙县人民医院总共收治的930例NSCLC患者，均行胸腔镜(VATS)肺切除术治疗，依据术后是否存在肺部感染分成感染组(n=76)与非感染组(n=854)。采用Logistic回归分析NSCLC术后发生肺部感染的影响因素；应用受试者工作特征(ROC)曲线评价术后24 h血清SAA、sCD14、sTREM-1单独及联合对NSCLC术后肺部感染发生的预测价值。结果 两组患者在TNM分期、肿瘤直径、ASA分级、糖尿病患病率方面比较，差异均具有统计学意义(P<0.05)。重复测量方差分析结果显示，组间、时间及交互效应差异均有统计学意义，感染组的血清SAA、sCD14及sTREM-1的整体水平显著高于非感染组(均P<0.001);两组患者的血清SAA、sCD14及sTREM-1水平在术后均随时间推移发生显著变化(P<0.001),与同组术前比较，两组在术后24 h及72 h的各指标水平均较术前升高(P<0.05);感染组患者术后各项指标的上升幅度大于非感染组。Logistic回归分析显示，糖尿病、血清SAA、sCD14、sTREM-1均为NSCLC术后发生肺部感染的影响因素(P<0.05)。ROC曲线分析显示，3项指标联合预测NSCLC术后发生肺部感染风险的效能最佳，AUC为0.899,约登指数高达0.826,灵敏度为91.11%,特异度为98.36%。结论 血清SAA、sCD14、sTREM-1与肺癌术后肺部感染的发生具有显著的关联性，3项联合检测可显著提升预测效能。

Objective To explore the value of serum amyloid A(SAA), soluble CD14(sCD14), and soluble triggering receptor expressed on myeloid cells-1(sTREM-1) for postoperative pulmonary infection after thoracoscopic lung resection in patients with non-small cell lung cancer(NSCLC). Methods A retrospective analysis was conducted on 930 NSCLC for patients admitted to Suzhou Guangci Cancer Hospital, Suzhou Municipal Hospital, and Xuyi County People's Hospital from January 2020 to September 2025, all of whom underwent video-assisted thoracoscopic surgery(VATS) lung resection. Based on the presence or absence of postoperative pulmonary infection, the patients were divided into an infection group(n=76) and a non-infection group(n=854). Logistic regression analysis was applied to examine the influencing factors for postoperative pulmonary infection after NSCLC. Receiver operating characteristic(ROC) curve analysis was performed to evaluate the predictive efficacy of serum SAA, sCD14, and sTREM-1 levels at 24 hours postoperatively, both individually and in combination, for the occurrence of postoperative pulmonary infection after NSCLC surgery. Results There were statistically significant differences between the two groups in terms of TNM stage, tumor diameter, ASA classification and the prevalence of diabetes(P<0.05). The results of repeated measures ANOVA showed that there were statistically significant differences inter-groups over time and in the interaction effect. The overall levels of serum SAA, sCD14 and sTREM-1 in the infection group were significantly higher than those in the non-infection group(all P<0.001). The levels of serum SAA, sCD14 and sTREM-1 in both groups changed significantly over time after surgery(P<0.001). Compared with the preoperative levels, the levels of each index in both groups at 24 and 72 hours after surgery were significantly higher(P<0.05). The increase in each index after surgery in the infection group was greater than that in the non-infection group. The Logistic regression model showed that diabetes, serum SAA, sCD14, and sTREM-1 were all influencing factors for the occurrence of postoperative pulmonary infection in NSCLC patients(P<0.05). ROC curve analysis revealed that the combined prediction of the three markers yielded the highest AUC(0.899), with a Youden index of 0.826, a sensitivity of 91.11%, and a specificity of 98.36%. Conclusion Serum SAA, sCD14, and sTREM-1 are significantly associated with the occurrence of pulmonary infection after lung cancer surgery. Combined detection of these three markers can significantly improve predictive efficacy.