厄洛替尼治疗晚期非小细胞肺癌分类及回归树分析

BACKGROUND AND OBJECTIVE: Erlotinib is a targeted therapy drug for non-small cell lung cancer (NSCLC). It has been proven that, there was evidence of various survival benefits derived from erlotinib in patients with different clinical features, but the results are conflicting. The aim of this study is to identify novel predictive factors and explore the interactions between clinical variables as well as their impact on the survival of Chinese patients with advanced NSCLC heavily treated with erlotinib. METHODS: The clinical and follow-up data of 105 Chinese NSCLC patients referred to the Cancer Hospital and Institute, Chinese Academy of Medical Sciences from September 2006 to September 2009 were analyzed. Multivariate analysis of progressive-free survival (PFS) was performed using recursive partitioning referred to as the classification and regression tree (CART) analysis. RESULTS: The median PFS of 105 eligible consecutive Chinese NSCLC patients was 5.0 months (95%CI: 2.9-7.1). CART analysis was performed for the initial, second, and third split in the lymph node involvement, the time of erlotinib administration, and smoking history. Four terminal subgroups were formed. The longer values for the median PFS were 11.0 months (95%CI: 8.9-13.1) for the subgroup with no lymph node metastasis and 10.0 months (95%CI: 7.9-12.1) for the subgroup with lymph node involvement, but not over the second-line erlotinib treatment with a smoking history ≤35 packs per year. The shorter values for the median PFS were 2.3 months (95%CI: 1.6-3.0) for the subgroup with lymph node metastasis and over the second-line erlotinib treatment, and 1.3 months (95%CI: 0.5-2.1) for the subgroup with lymph node metastasis, but not over the second-line erlotinib treatment with a smoking history >35 packs per year. CONCLUSION: Lymph node metastasis, the time of erlotinib administration, and smoking history are closely correlated with the survival of advanced NSCLC patients with first- to third-line erlotinib treatment. CART can identify previously unappreciated patient subsets and is advantageous for identifying homogeneous patient populations in clinical practice and future clinical trials.