Li Hongwei, Lian Jianhong, Han Songyan, Wang Weili, Jia Haixia, Cao Jianzhong, Zhang Xiaqin, Song Xin, Jia Sufang, Ren Jiwei, Yang Weihua, Xi Yanfeng, Lan Shengmin
Department of Radiation Oncology, Shanxi Provincial Cancer Hospital, Shanxi Medical University, Taiyuan, Shanxi Province 030013, People's Republic of China.
Department of Surgery, Shanxi Provincial Cancer Hospital, Shanxi Medical University, Taiyuan, Shanxi Province 030013, People's Republic of China.
Oncotarget. 2017 Aug 7;8(41):70727-70735. doi: 10.18632/oncotarget.19980. eCollection 2017 Sep 19.
Several scoring systems are available to estimate prognosis and assist in selecting treatment methods for non-small cell lung cancer (NSCLC) patients with brain metastasis, including recursive partitioning analysis (RPA), basic score for brain metastases (BS-BM), and diagnosis-specific graded prognostic assessment (DS-GPA). Lung-molGPA is an update of the DS-GPA that incorporates EGFR and/or ALK mutation status. The present study tested the applicability of these four indexes in 361 lung adenocarcinoma patients with brain metastasis. Potential predictive factors in our independent multivariate analysis included patient age, Karnofsky performance status, EGFR and ALK mutation status, and use of targeted therapy. In the log-rank test, all four systems predicted overall survival (OS) (<0.001). Harrells C indexes were 0.732, 0.724, 0.729, and 0.747 for RPA, BS-BM, DS-GPA, and Lung-molGPA, respectively. Our results confirmed that the Lung-molGPA index was useful for estimating OS in our patient cohort, and appeared to provide the most accurate predictions. However, the independent prognostic factors identified in our study were not entirely in agreement with the Lung-molGPA factors. In an era of targeted therapy, Lung-molGPA must be further updated to incorporate more specific prognostic factors based on additional patient data.
有几种评分系统可用于评估非小细胞肺癌（NSCLC）脑转移患者的预后并协助选择治疗方法，包括递归分区分析（RPA）、脑转移基本评分（BS-BM）和诊断特异性分级预后评估（DS-GPA）。Lung-molGPA是DS-GPA的更新版本，纳入了EGFR和/或ALK突变状态。本研究测试了这四种指标在361例肺腺癌脑转移患者中的适用性。我们独立多变量分析中的潜在预测因素包括患者年龄、卡诺夫斯基功能状态、EGFR和ALK突变状态以及靶向治疗的使用情况。在对数秩检验中，所有四种系统都能预测总生存期（OS）（<0.001）。RPA、BS-BM、DS-GPA和Lung-molGPA的Harrells C指数分别为0.732、0.724、0.729和0.747。我们的结果证实，Lung-molGPA指数对于估计我们患者队列中的总生存期是有用的，并且似乎能提供最准确的预测。然而，我们研究中确定的独立预后因素与Lung-molGPA因素并不完全一致。在靶向治疗时代，Lung-molGPA必须进一步更新，以纳入基于更多患者数据的更具体的预后因素。
