| 唐江洪,雷晓红,黄宇香,蔡开赛,李 男.基于血清CEA、GPX3、CXCL9构建非小细胞肺癌患者根治术后早期复发转移的预测模型[J].,2024,(10):1941-1945 |
| 基于血清CEA、GPX3、CXCL9构建非小细胞肺癌患者根治术后早期复发转移的预测模型 |
| Construction of Prediction Model for Early Recurrence and Metastasis of Non-Small Cell Lung Cancer Patients after Radical Surgery Based on Serum CEA, GPX3 and CXCL9 |
| 投稿时间：2023-12-06 修订日期：2023-12-28 |
| DOI：10.13241/j.cnki.pmb.2024.10.029 |
| 中文关键词: CEA GPX3 CXCL9 非小细胞肺癌 肺癌根治术 复发转移 预测模型 |
| 英文关键词: CEA GPX3 CXCL9 Non-small cell lung cancer Radical resection of lung cancer Recurrence and metastasis Prediction model |
| 基金项目:湖南省中医药科研计划项目（201821） |
|
| 摘要点击次数: 83 |
| 全文下载次数: 89 |
| 中文摘要: |
| 摘要 目的：基于血清癌胚抗原（CEA）、谷胱甘肽过氧化物酶3（GPX3）、CXC趋化因子配体9（CXCL9）构建非小细胞肺癌（NSCLC）患者根治术后早期复发转移的预测模型。方法：选取2018年7月-2019年12月于湖南中医药大学第二附属医院行肺癌根治术的95例NSCLC患者。采用酶联免疫吸附法检测血清CEA、GPX3、CXCL9水平。术后行3年随访，根据随访期间患者有无发生复发转移分为未复发转移组与复发转移组。Logistic回归模型分析NSCLC患者术后复发转移的影响因素，并建立NSCLC患者根治术后早期复发转移预测模型。采用受试者工作特征（ROC）曲线分析预测模型的预测效能。结果：术后随访3年，95例患者失访2例，复发转移36例。复发转移组血清CEA、CXCL9水平高于未复发转移组，GPX3水平低于未复发转移组（P＜0.05）。复发转移组与未复发转移组在肿瘤类型、TNM分期、淋巴结清扫数方面，差异比较具有统计学意义（P＜0.05）。Logistic回归模型结果显示，TNM分期、淋巴结清扫数及血清CEA、GPX3、CXCL9水平为NSCLC患者术后复发转移的影响因素（P＜0.05）。ROC分析结果显示，Log P 预测模型的ROC-AUC（0.95CI）为0.862（0.772～0.943）。结论：血清CEA、CXCL9水平上升，GPX3水平下降为NSCLC肺癌根治术后患者复发转移的影响因素。血清CEA、CXCL9、GPX3联合构建的预测模型可辅助预测NSCLC术后复发转移风险。 |
| 英文摘要: |
| ABSTRACT Objective: To construct a prediction model for early recurrence and metastasis of non-small cell lung cancer (NSCLC) patients after radical surgery based on serum carcinoembryonic antigen (CEA), glutathione peroxidase 3 (GPX3) and C-X-C chemokine ligand 9 (CXCL9). Methods: 95 cases of NSCLC patients who underwent radical resection of lung cancer in the Second Affiliated Hospital of Hunan University of Traditional Chinese Medicine from July 2018 to December 2019 were selected. Serum CEA, GPX3 and CXCL9 levels were detected by enzyme-linked immunosorbent assay. The patients were followed up for 3 years after the surgery, according to the occurrence of recurrence and metastasis during the follow-up period, the patients were divided into non-recurrence and metastasis group and recurrence and metastasis group. Logistic regression model analysis of influencing factors of postoperative recurrence and metastasis in NSCLC patients, and the prediction model of early recurrence and metastasis in NSCLC patients after radical surgery was established. The predictive efficiency of the prediction model was analyzed by receiver operating characteristic (ROC) curve. Results: After 3 years of follow-up, 2 cases of 95 patients were lost to follow-up, there were 36 cases of recurrence and metastasis. Serum CEA and CXCL9 levels in the recurrence and metastasis were higher than those in the non-recurrence and metastasis group, and GPX3 level was lower than that in the non-recurrence and metastasis group (P＜0.05). There were statistically significant differences in tumor type, TNM stage and lymph node dissection count between the recurrence and metastasis group and the non-recurrence and metastasis group(P＜0.05). Logistic regression model showed that TNM stage, lymph node dissection count and serum CEA, GPX3 and CXCL9 levels were influencing factors of postoperative recurrence and metastasis in NSCLC patients(P＜0.05). ROC-AUC (0.95CI) of Log P prediction model was 0.862 (0.772~0.943). Conclusion: The increase of serum CEA and CXCL9 levels, and the decrease of GPX3 level are influencing factors for recurrence and metastasis in NSCLC patients after radical resection of lung cancer. The prediction model constructed by combining the Serum CEA, CXCL9, and GPX3 can assist in predicting the risk of recurrence and metastasis of NSCLC after radical resection of lung cancer. |
|
查看全文
查看/发表评论 下载PDF阅读器 |
| 关闭 |
