Zhang Kai, Shi Liang, Zhang Tongmei, Tong Li, Wei Song, Li Hongxia
Department of Medical Oncology, Beijing Tuberculosis & Thoracic Tumor Research Institute/Beijing Chest Hospital, Capital Medical University, Beijing 101149, China.
Laboratory for Clinical Medicine, Capital Medical University, Beijing 101149, China.
Zhongguo Fei Ai Za Zhi. 2024 Dec 20;27(12):894-902. doi: 10.3779/j.issn.1009-3419.2024.101.32.
Immunotherapy has been a standard treatment for the patients with advanced non-small cell lung cancer (NSCLC), however, reliable biomarkers for predicting the response remain unclear. This study explores the subpopulations of lymphocytes in bronchoalveolar lavage fluid (BALF) and combines clinical and laboratory examination indicators of NSCLC patients to identify potential biomarkers related to immunotherapy.
A retrospective analysis was conducted on 82 patients with locally advanced or metastatic NSCLC who underwent electronic bronchoscopy and received first-line immunotherapy at Beijing Chest Hospital, Capital Medical University between March 2020 and November 2022. Logistic regression and random forest models were employed to determine the correlation between immune cell subsets in BALF and response of immunotherapy. The predictive value was validated by the model.
All patients enrolled received first-line immunotherapy, and the efficacy was evaluated according to clinical guidelines: among the 82 patients included, 48 patients got objective response and the other 34 did not achieve. The relationship between collected indicators and the best clinical treatment response was analyzed. The result shows that a higher percentage of total lymphocytes in BALF was associated with good response of first-line immunotherapy (P<0.05), while a higher percentage of T helper cells in BALF was associated with poor prognosis (P<0.05).
The proportions of total lymphocytes and T helper cells in BALF could be used as predictive biomarkers for first-line immunotherapy in late stage NSCLC. A multivariable model improves predictive accuracy.
免疫疗法一直是晚期非小细胞肺癌(NSCLC)患者的标准治疗方法,然而,用于预测疗效的可靠生物标志物仍不明确。本研究探讨支气管肺泡灌洗液(BALF)中淋巴细胞亚群,并结合NSCLC患者的临床和实验室检查指标,以识别与免疫疗法相关的潜在生物标志物。
对2020年3月至2022年11月期间在北京胸科医院、首都医科大学接受电子支气管镜检查并接受一线免疫治疗的82例局部晚期或转移性NSCLC患者进行回顾性分析。采用逻辑回归和随机森林模型确定BALF中免疫细胞亚群与免疫治疗反应之间的相关性。通过该模型验证预测价值。
所有纳入患者均接受一线免疫治疗,并根据临床指南评估疗效:在纳入的82例患者中,48例获得客观缓解,其余34例未达到。分析收集的指标与最佳临床治疗反应之间的关系。结果显示,BALF中总淋巴细胞百分比越高,与一线免疫治疗的良好反应相关(P<0.05),而BALF中辅助性T细胞百分比越高,与预后不良相关(P<0.05)。
BALF中总淋巴细胞和辅助性T细胞的比例可作为晚期NSCLC一线免疫治疗的预测生物标志物。多变量模型可提高预测准确性。