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246例非小细胞肺癌的预后影响因素分析
引用本文:方志红,李天苗,许荣忠,吴建春,李雁. 246例非小细胞肺癌的预后影响因素分析[J]. 现代肿瘤医学, 2017, 0(8): 1234-1236. DOI: 10.3969/j.issn.1672-4992.2017.08.015
作者姓名:方志红  李天苗  许荣忠  吴建春  李雁
作者单位:1. 上海中医药大学附属市中医医院肿瘤科,上海,200071;2. 北京市中医医院顺义医院肿瘤科,北京,101300
基金项目:上海市卫生局科研课题项目(20134351),上海市卫生和计划生育委员会中医药科研基金项目(2014LP075A)
摘    要:目的:分析246例非小细胞肺癌(non-small cell lung cancer,NSCLC)患者的预后影响因素.方法:回顾性分析2010年1月至2014年12月246例非小细胞肺癌患者临床资料,采用Kaplan-Meier法进行生存分析,Log-rank检验和Cox模型预后影响因素行单因素和多因素分析.结果:全组患者中位生存时间为37.44个月.1年、3年、5年总生存率分别为72%、46%、26%.单因素分析显示,男性、年龄>75岁、晚期、有吸烟史、有肝转移、无手术史非小细胞肺癌患者的中位生存期明显缩短(P<0.05或P<0.01).多因素分析显示,性别、疾病分期、是否吸烟和是否手术是影响非小细胞肺癌预后的独立因素(P <0.05或P<0.01).结论:性别、疾病分期、是否吸烟和是否手术是非小细胞肺癌的独立预后因素.

关 键 词:非小细胞肺癌  生存分析  预后因素

Analysis of prognostic factors in 246 patients with non-small cell lung cancer
Fang Zhihong,Li Tianmiao,Xu Rongzhong,Wu Jianchun,Li Yan. Analysis of prognostic factors in 246 patients with non-small cell lung cancer[J]. Journal of Modern Oncology, 2017, 0(8): 1234-1236. DOI: 10.3969/j.issn.1672-4992.2017.08.015
Authors:Fang Zhihong  Li Tianmiao  Xu Rongzhong  Wu Jianchun  Li Yan
Abstract:Objective:To analyze prognostic factors in non-small cell lung cancer(NSCLC).Methods:The data of 246 patients with NSCLC from January 2010 to December 2014 were analyzed in this study.Kaplan-Meier method was used for survival analysis,and Log-rank test and Cox regression were used for univariate and multivariate analyses of prognostic factors.Results:The median survival time of all patients was 37.44 months.The 1-,3-,and 5-year overall survival rates were 72%,46% and 26%,respectively.The univariate analysis showed male,age > 75 years old,advanced,smoking,liver metastases,no surgery reduced the overall survival time in patients with NSCLC.The multivariate analysis showed that gender,disease stage,pathological types,taking surgery were independent factors affecting the prognosis for NSCLC patients.Conclusion:Gender,disease stage,smoking history,surgery history were independent factors for the overall survival of NSCLC.
Keywords:non-small cell lung cancer  survival analysis  prognostic factors
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