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术后抑郁及免疫炎症生物标志物对接受微创食管癌切除术患者预后的影响:一项基于中国人群的回顾性队列研究

Impact of postoperative depression and immune-inflammatory biomarkers on the prognosis of patients with esophageal cancer receiving minimally invasive esophagectomy: a retrospective cohort study based on a Chinese population.

作者信息

Tan Pei-Xin, Wu Lin-Xin, Ma Shuang, Wei Shi-Jing, Wang Tai-Hang, Wang Bing-Chen, Fu Bing-Bing, Yang Jia-Shuo, Zhao Qing, Sun Li, Liu Yi, Yan Tao

机构信息

Department of Anesthesiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

School of Information Science and Engineering, Shenyang Ligong University, Shenyang, China.

出版信息

Front Immunol. 2025 Jun 6;16:1610267. doi: 10.3389/fimmu.2025.1610267. eCollection 2025.

Abstract

BACKGROUND

Patients with esophageal cancer (EC) frequently experience depression following neoadjuvant therapy and surgery, a condition that may trigger systemic inflammation, suppress antitumor immunity, and alter immune-inflammatory pathways in the tumor microenvironment (TME), potentially contributing to residual tumor progression and theoretically worsening patient prognosis. This study aimed to investigate the interrelationship between depression and prognosis in patients with EC, with a focus on immune-inflammatory biomarkers.

METHODS

This single-center retrospective trial was conducted at the National Cancer Center/Cancer Hospital of the Chinese Academy of Medical Sciences. A total of 319 patients who underwent minimally invasive esophagectomy between November 2023 and December 2024 were enrolled. Least absolute shrinkage and selection operator (LASSO) regression in combination with multivariate Cox and logistic regression were employed to identify the main impact indicators of relapse-free survival (RFS) and depression. The developed predictive model was evaluated using calibration plots, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). Internal validation was carried out using a 7:3 data split.

RESULTS

LASSO and Cox regression identified clinical stage (hazard ratio [HR]=2.472, P=0.003), the preoperative systemic inflammatory index (SII, HR=1.001, P<0.001), and depression severity (HR=2.398, P=0.004) as independent predictors of RFS. Based on these variables, a predictive model for RFS was constructed utilizing multivariate logistic regression and visualized as a nomogram. The model demonstrated good discriminative ability, with the areas under the ROC curves (AUCs) of 0.826 (6 months) and 0.773 (12 months) in the training set and 0.817 (6 months) and 0.789 (12 months) in the validation set. The incidence of postoperative depression in the study cohort was 28.2%, with chronic postsurgical pain identified as the sole independent risk factor for depression.

CONCLUSION

This study revealed that preoperative immune-inflammatory biomarkers and postoperative depression significantly affect patient prognosis after minimally invasive esophagectomy. Our work has also provided new insight into the individualized and comprehensive management of patients with EC, underscoring the necessity for comprehensive psychosocial interventions alongside conventional anticancer therapies to optimize clinical endpoints.

摘要

背景

食管癌(EC)患者在新辅助治疗和手术后常出现抑郁,这种情况可能引发全身炎症,抑制抗肿瘤免疫力,并改变肿瘤微环境(TME)中的免疫炎症途径,可能导致残留肿瘤进展,并在理论上恶化患者预后。本研究旨在探讨EC患者抑郁与预后之间的相互关系,重点关注免疫炎症生物标志物。

方法

本单中心回顾性试验在中国医学科学院肿瘤医院/国家癌症中心进行。共纳入2023年11月至2024年12月期间接受微创食管切除术的319例患者。采用最小绝对收缩和选择算子(LASSO)回归结合多变量Cox和逻辑回归来确定无复发生存期(RFS)和抑郁的主要影响指标。使用校准图、受试者工作特征(ROC)曲线和决策曲线分析(DCA)对所建立的预测模型进行评估。采用7:3的数据分割进行内部验证。

结果

LASSO和Cox回归确定临床分期(风险比[HR]=2.472,P=0.003)、术前全身炎症指数(SII,HR=1.001,P<0.001)和抑郁严重程度(HR=2.398,P=0.004)为RFS的独立预测因素。基于这些变量,利用多变量逻辑回归构建了RFS预测模型,并将其可视化为列线图。该模型显示出良好的判别能力,训练集中6个月和12个月时ROC曲线下面积(AUC)分别为0.826和0.773,验证集中分别为0.817和0.789。研究队列中术后抑郁的发生率为28.2%,慢性术后疼痛被确定为抑郁的唯一独立危险因素。

结论

本研究表明,术前免疫炎症生物标志物和术后抑郁显著影响微创食管切除术后患者的预后。我们的工作还为EC患者的个体化和综合管理提供了新的见解,强调了在传统抗癌治疗的同时进行全面心理社会干预以优化临床终点的必要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c9a/12179172/4dfb5725d133/fimmu-16-1610267-g001.jpg

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