Gao Jiani, Ren Yijiu, Guo Haoyue, Mao Rui, Xie Huikang, Su Hang, She Yunlang, Deng Jiajun, Yang Minglei, Han Biao, Zhang Yu, Li Jian, Xie Dong, Chen Chang
Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai 200443, China.
School of Medicine, Tongji University, Shanghai 200092, China.
Ann Transl Med. 2020 Apr;8(7):470. doi: 10.21037/atm.2020.03.113.
The prognosis of patients with stage I non-small cell lung cancer (NSCLC) is often uncertain. This study aims to investigate a new prognostic tool to classify stage I NSCLC patients more accurately.
CD68 and CD163 macrophages were quantified by immunohistochemical analyses of the center of the tumor and the invasive margin of the 339 tumors, which were used to construct the macrophage immunoscore (MI). Cox proportional hazards models determined the effects of multiple factors on disease-free survival (DFS) and overall survival (OS). One nomogram was developed to predict DFS and OS of stage I patients.
The multivariate Cox analysis identified MI (P<0.001), lymphocyte-to-monocyte ratio (LMR, P=0.006), and TNM stage (P=0.046) as independent prognostic factors for DFS. Compared with MI, TNM stage, and LMR alone, the nomogram improved the prediction accuracy of both DFS and OS in terms of the Harrell concordance index in the training cohort (0.812, P<0.001 for DFS; 0.810, P<0.001 for OS) and the external validation cohort (0.796, P<0.001 for DFS; 0.791, P<0.001 for OS). In addition, net reclassification (Nomogram TNM-stage, P<0.001 for DFS and OS) and the integrated discrimination (Nomogram TNM stage, P<0.001 for DFS and OS) also validated this improvement.
The immunoscore-based prognostic nomogram could effectively predict DFS and OS of stage I NSCLC patients and enhance the predictive value of the TNM stage system.
Ⅰ期非小细胞肺癌(NSCLC)患者的预后通常不确定。本研究旨在探索一种新的预后工具,以更准确地对Ⅰ期NSCLC患者进行分类。
通过对339个肿瘤的肿瘤中心和浸润边缘进行免疫组织化学分析,对CD68和CD163巨噬细胞进行定量,用于构建巨噬细胞免疫评分(MI)。Cox比例风险模型确定多种因素对无病生存期(DFS)和总生存期(OS)的影响。开发了一个列线图来预测Ⅰ期患者的DFS和OS。
多变量Cox分析确定MI(P<0.001)、淋巴细胞与单核细胞比值(LMR,P=0.006)和TNM分期(P=0.046)为DFS的独立预后因素。与单独的MI、TNM分期和LMR相比,列线图在训练队列(DFS的Harrell一致性指数为0.812,P<0.001;OS的Harrell一致性指数为0.810,P<0.001)和外部验证队列(DFS的Harrell一致性指数为0.796,P<0.001;OS的Harrell一致性指数为0.791,P<0.001)中提高了DFS和OS的预测准确性。此外,净重新分类(列线图对比TNM分期,DFS和OS的P<0.001)和综合判别(列线图对比TNM分期,DFS和OS的P<0.001)也验证了这种改善。
基于免疫评分的预后列线图可以有效预测Ⅰ期NSCLC患者的DFS和OS,并提高TNM分期系统的预测价值。