Xie Yuyan, Shi Zhihao, Chen Tong, Li Hongyan, Fan Menglin, Xiang Xuqin, Liu Fang
Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Front Immunol. 2025 Apr 16;16:1567565. doi: 10.3389/fimmu.2025.1567565. eCollection 2025.
Neoadjuvant immunochemotherapy (nICT) has significantly improved event-free survival (EFS) and pathologic complete response (pCR) in patients with resectable non-small cell lung cancer (NSCLC). However, the lack of validated biomarkers limits their ability to predict therapeutic efficacy and survival outcomes. This study aimed to develop a novel inflammatory and nutritional index, the Lung Cancer Immune Prognostic Score (LCIPS), to predict pCR and survival prognosis in patients with NSCLC.
This retrospective study included 131 patients with clinical stage IB-IIIB NSCLC who underwent neoadjuvant immunochemotherapy between May 2020 and May 2024. Baseline clinical data and hematological parameters were collected. Lasso regression analysis was employed to identify hematological indices associated with pCR, and the LCIPS was constructed based on these factors. Kaplan-Meier survival analysis and log-rank tests were used to assess survival differences. Logistic regression was performed to identify the predictors of pCR, while Cox regression analysis determined independent prognostic factors for disease-free survival (DFS) and overall survival (OS). The predictive performance of the LCIPS was validated using a nomogram.
Lasso regression identified three core hematological indices: the albumin-to-globulin ratio (A/G), absolute monocyte count (MONO), and absolute lymphocyte count (LYM). The LCIPS formula was as follows: LCIPS=0.900×A/G+0.761×MONO (10/L) -0.065×LYM (10/L). Receiver operating characteristic (ROC) curve analysis showed that the LCIPS had superior predictive efficacy (area under the curve (AUC) = 0.68) compared to other classical markers. Univariate and multivariate logistic regression analyses identified intraoperative lymph node dissection status and A/G and LCIPS as independent predictors of pCR ( < 0.05). Multivariate Cox regression analysis demonstrated that smoking status and LCIPS were independent prognostic factors for DFS and OS. Nomogram validation indicated robust predictive accuracy for LCIPS. Notably, among immune-related adverse events (irAEs), endocrine- and cardiac-related irAEs significantly affected DFS ( < 0.05).
LCIPS is an independent predictor of pCR in patients with NSCLC receiving neoadjuvant immunochemotherapy and is associated with improved DFS and survival outcomes. This novel index offers valuable guidance for personalized treatment strategies.
新辅助免疫化疗(nICT)显著改善了可切除非小细胞肺癌(NSCLC)患者的无事件生存期(EFS)和病理完全缓解率(pCR)。然而,缺乏经过验证的生物标志物限制了其预测治疗效果和生存结果的能力。本研究旨在开发一种新的炎症和营养指标,即肺癌免疫预后评分(LCIPS),以预测NSCLC患者的pCR和生存预后。
本回顾性研究纳入了2020年5月至2024年5月期间接受新辅助免疫化疗的131例临床分期为IB-IIIB期的NSCLC患者。收集基线临床数据和血液学参数。采用Lasso回归分析确定与pCR相关的血液学指标,并基于这些因素构建LCIPS。采用Kaplan-Meier生存分析和对数秩检验评估生存差异。进行逻辑回归以确定pCR的预测因素,而Cox回归分析确定无病生存期(DFS)和总生存期(OS)的独立预后因素。使用列线图验证LCIPS的预测性能。
Lasso回归确定了三个核心血液学指标:白蛋白与球蛋白比值(A/G)、绝对单核细胞计数(MONO)和绝对淋巴细胞计数(LYM)。LCIPS公式如下:LCIPS = 0.900×A/G + 0.761×MONO(10/L)- 0.065×LYM(10/L)。受试者工作特征(ROC)曲线分析表明,与其他经典标志物相比,LCIPS具有更好的预测效能(曲线下面积(AUC)= 0.68)。单因素和多因素逻辑回归分析确定术中淋巴结清扫状态以及A/G和LCIPS为pCR的独立预测因素(< 0.05)。多因素Cox回归分析表明,吸烟状态和LCIPS是DFS和OS的独立预后因素。列线图验证表明LCIPS具有强大的预测准确性。值得注意的是,在免疫相关不良事件(irAE)中,内分泌和心脏相关的irAE显著影响DFS(< 0.05)。
LCIPS是接受新辅助免疫化疗的NSCLC患者pCR的独立预测因素,并与改善的DFS和生存结果相关。这一新指标为个性化治疗策略提供了有价值的指导。