Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital, Guangdong Key Laboratory of Lung Cancer Translational Medicine, South China University of Technology & Guangdong Academy of Medical Sciences, Guangzhou, 510080, China.
BMC Cancer. 2019 Nov 6;19(1):1051. doi: 10.1186/s12885-019-6216-x.
Local consolidative treatment (LCT) is important for oligometastasis, defined as the restricted metastatic capacity of a tumor. This study aimed to determine the effects and prognostic heterogeneity of LCT in oligometastatic non-small cell lung cancer.
This retrospective study identified 436 eligible patients treated for oligometastatic disease at the Guangdong Provincial People's Hospital during 2009-2016. A Cox regression analysis was used to identify potential predictors of overall survival (OS). After splitting cases randomly into training and testing sets, risk stratification was performed using recursive partitioning analysis with a training dataset. The findings were confirmed using a validation dataset. The effects of LCT in different risk groups were evaluated using the Kaplan-Meier method.
The T stage (p = 0.001), N stage (p = 0.008), number of metastatic sites (p = 0.031), and EGFR status (p = 0.043) were identified as significant predictors of OS. A recursive partitioning analysis was used to establish a prognostic risk model with the following four risk groups: Group I included never smokers with N0 disease (3-year OS: 55.6%, median survival time [MST]: 42.8 months), Group II included never smokers with N+ disease (3-year OS: 32.8%, MST: 26.5 months), Group III included smokers with T0-2 disease (3-year OS: 23.3%, MST: 19.4 months), and Group IV included smokers with T3/4 disease (3-year OS: 12.5%, MST: 11.1 months). Significant differences in OS according to LCT status were observed in all risk groups except Group IV (p = 0.45).
Smokers with T3/4 oligometastatic non-small cell lung cancer may not benefit from LCT.
局部巩固治疗(LCT)对于寡转移,即肿瘤的有限转移能力,非常重要。本研究旨在确定 LCT 在寡转移性非小细胞肺癌中的作用和预后异质性。
本回顾性研究纳入了 2009 年至 2016 年期间在广东省人民医院接受寡转移疾病治疗的 436 名符合条件的患者。采用 Cox 回归分析确定总生存期(OS)的潜在预测因素。将病例随机分为训练集和测试集后,使用递归分区分析对训练数据集进行风险分层。使用验证数据集进行验证。使用 Kaplan-Meier 方法评估 LCT 在不同风险组中的作用。
T 分期(p=0.001)、N 分期(p=0.008)、转移灶数量(p=0.031)和 EGFR 状态(p=0.043)被确定为 OS 的显著预测因素。递归分区分析建立了一个预后风险模型,包含以下四个风险组:I 组包括从不吸烟且无 N 期疾病的患者(3 年 OS:55.6%,中位生存时间[MST]:42.8 个月);II 组包括从不吸烟且有 N+期疾病的患者(3 年 OS:32.8%,MST:26.5 个月);III 组包括吸烟且 T0-2 期疾病的患者(3 年 OS:23.3%,MST:19.4 个月);IV 组包括吸烟且 T3/4 期疾病的患者(3 年 OS:12.5%,MST:11.1 个月)。除了 IV 组(p=0.45)外,所有风险组中 LCT 状态对 OS 的影响均有显著差异。
吸烟且 T3/4 期寡转移性非小细胞肺癌患者可能不能从 LCT 中获益。