【作者】 赵宇；

【导师】 李泽坚； 郭惠琴；

【作者基本信息】 北京协和医学院 ， 临床医学， 2013， 博士

【摘要】 目的肺癌是当今世界上肿瘤相关死亡率最高的恶性肿瘤,非小细胞肺癌占其中的绝大多数。脑转移在非小细胞肺癌患者中较为常见且是肿瘤复发转移最重要的原因之一。但是,直到现在为止,并没有一种可以简明、准确的预测非小细胞肺癌脑转移的方法。在这篇论文中,我们探索了中国人群中表皮生长因子受体(EGFR)和KRAS基因突变与非小细胞肺癌脑转移风险的关系,并且利用某些临床风险因子和这些基因突变去建立一个非小细胞肺癌脑转移预测模型。方法我们的研究是一项回顾性研究,一共收集了191例主要治疗过程在北京协和医院完成的中国非小细胞肺癌患者。我们收集和分析的信息包括EGFR和KRAS基因突变,临床资料包括首诊时的性别,年龄,组织学,原发灶位置,吸烟史,肿瘤分期和淋巴结转移情况等。单因素coX回归模型和多因素coX回归模型先后用于研究EGFR和KRAS基因突变及临床风险因子对非小细胞肺癌脑转移风险的影响。利用这些基因突变和临床参数,及在多因素分析中获取的系数,我们将建立脑转移的风险预测模型。结果一共有26位患者在随访过程中发生了脑转移,占研究人群的13.6%。统计结果显示EGFR基因突变(P=0.030),小于等于60岁的年龄(P=0.043)和淋巴结转移(P=0.020)能显著增加非小细胞肺癌患者罹患脑转移的风险。我们利用上述结果,即EGFR基因突变,年龄和淋巴结转移情况,建立了非小细胞肺癌脑转移预测模型和风险积分,并且区分出脑转移的高、中、低危风险组。脑转移高、中、低危风险组3年脑转移发生率估计为30.1%,20.5%和1.5%,具有预测意义(P<0.001)。结论EGFR基因突变,小于等于60岁的年龄和淋巴结转移与非小细胞肺癌脑转移风险增加相关。我们利用这个发现建立的非小细胞肺癌脑转移预测模型有显著的预测意义。未来的医疗实践中,对有EGFR突变等高危因素的非小细胞肺癌脑转移高危患者应予密切随诊。关于非小细胞肺癌脑转移预防性治疗(包括预防性全脑放射治疗或靶向治疗)的临床研究应予倡导。更多还原

【Abstract】 Purpose:Lung cancer is the leading cause of tumor-related death worldwide and most of them are non-small cell lung cancer (NSCLC). Brain metastases are common in patients with non-small cell lung cancer and they are one of the most important causes of tumor relapse. However, nowthere is not any concise and accurate predictive method to judge which NSCLC patient may develop brain metastasis.In this study weinvestigatedthe association between EGFR and KRAS mutation and the risk of developing brain metastasis in a cohort of Chinese NSCLC patientsand made a risk prediction model fordevelopingbrain metastasis in NSCLCwiththe use of both genetic mutations and clinical covariates.Methods:Altogether191Chinese patients with NSCLCwho have accepted majority of their treatment at Peking Union Medical College Hospital were enrolled in this retrospectivestudy. EGFR and KRAS mutation status and Clinical information including gender, age, cell type, primary location of tumor, smoking history, tumor stage, lymph node metastasis at the time of diagnosis of NSCLCwere obtained and analyzed. Univariate and multivariate Cox regression model was used successivelyto investigatehow EGFR and KRAS mutations and clinical risk factors affected the risk ofbrain metastasis in NSCLC patients. A risk prediction model using genetic mutations and clinical risk factors with the parameter obtained in multivariate Cox regression analysis was established.Results:A total of26(13.6%) patients were diagnosed with brain metastases during the follow-up period. EGFR mutation (P=0.030), younger age (≤60years)(P=0.043) and lymph node metastasis (P=0.020) were found tosignif icantly increase the risk of developing brain metastasis among NSCLC patients. The prediction modelor risk prediction score for brain metastasis was made and high, intermediate, and low risk group were ranked. The3-year estimating of having brain metastasis for high, intermediate and low risk group was30.1%,20.5%and1.5%, respectively, stratifiedby EGFR mutation, age and lymph node metastasis(P<0.001).Conclusion:EGFR mutation, younger age≤60years and lymph node metastasis are significantlyassociated with the increasingrisk of developing brain metastasis in NSCLC patients. And the prediction model based on this discover is useful. In the future, NSCLC patients with positive EGFR mutation at high risk for brain metastasis should be considered for close surveillance. And trials of prophylactic therapy using targeted agents or prophylactic cranial irradiation (PCI) therapy should be developed.更多还原