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首页> 外文期刊>BMC Cancer >Is there a subgroup of long-term evolution among patients with advanced lung cancer?: Hints from the analysis of survival curves from cancer registry data
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Is there a subgroup of long-term evolution among patients with advanced lung cancer?: Hints from the analysis of survival curves from cancer registry data

机译:晚期肺癌患者中是否存在长期进化的亚组?:根据癌症登记数据对生存曲线的分析提示

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Background Recently, with the access of low toxicity biological and targeted therapies, evidence of the existence of a long-term survival subpopulation of cancer patients is appearing. We have studied an unselected population with advanced lung cancer to look for evidence of multimodality in survival distribution, and estimate the proportion of long-term survivors. Methods We used survival data of 4944 patients with non-small-cell lung cancer (NSCLC) stages IIIb–IV at diagnostic, registered in the National Cancer Registry of Cuba (NCRC) between January 1998 and December 2006. We fitted one-component survival model and two-component mixture models to identify short- and long- term survivors. Bayesian information criterion was used for model selection. Results For all of the selected parametric distributions the two components model presented the best fit. The population with short-term survival (almost 4?months median survival) represented 64% of patients. The population of long-term survival included 35% of patients, and showed a median survival around 12?months. None of the patients of short-term survival was still alive at month 24, while 10% of the patients of long-term survival died afterwards. Conclusions There is a subgroup showing long-term evolution among patients with advanced lung cancer. As survival rates continue to improve with the new generation of therapies, prognostic models considering short- and long-term survival subpopulations should be considered in clinical research.
机译:背景技术近来,随着低毒性生物疗法和靶向疗法的进入,出现了癌症患者长期生存亚群的存在的证据。我们研究了未选的晚期肺癌人群,以寻找生存分布多模态的证据,并估计长期幸存者的比例。方法我们使用了1998年1月至2006年12月在古巴国家癌症登记局(NCRC)注册的4944例非小细胞肺癌(NSCLC)IIIb-IV期患者的生存数据。模型和两成分混合模型来识别短期和长期幸存者。贝叶斯信息准则用于模型选择。结果对于所有选定的参数分布,两个组件模型显示出最佳拟合。短期生存(中位生存期将近4个月)的人群占64%。长期生存的人群包括35%的患者,并且中位生存期约为12个月。短期生存的患者中没有一个在第24个月还活着,而长期生存的患者中有10%之后死亡。结论有一个亚组显示晚期肺癌患者的长期演变。随着新一代疗法的存活率不断提高,在临床研究中应考虑考虑短期和长期存活亚群的预后模型。

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