Interaction trees with censored survival data.
Interaction trees with censored survival data.
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DOI：
10.2202/1557-4679.1071
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发表时间：
2008-01-28
期刊：
影响因子：
--
通讯作者：
Yang, Song
中科院分区：
文献类型：
--
作者：
Su, Xiaogang;Zhou, Tianni;Yang, Song
我们提出了一种交互树（IT）程序来优化涉及审查生存时间的比较研究中的亚组分析。所提出的方法递归地将数据划分为与治疗相互作用最大的两个子集，这导致了许多客观定义的子组：在其中一些治疗效果突出，而在其他治疗可能具有可忽略不计甚至负面的影响。由此产生的树状结构可用于探索治疗和其他协变量之间的整体相互作用，并有助于识别和描述实验治疗显示预期疗效的可能目标人群。我们遵循标准的CART （Breiman, et al., 1984）方法来开发交互树结构。通过交互树的随机森林提取变量重要性信息。模拟实验和原发性胆汁性肝硬化（PBC）数据的分析提供了评估和说明所提出的程序。
We propose an interaction tree (IT) procedure to optimize the subgroup analysis in comparative studies that involve censored survival times. The proposed method recursively partitions the data into two subsets that show the greatest interaction with the treatment, which results in a number of objectively defined subgroups: in some of them the treatment effect is prominent while in others the treatment may have a negligible or even negative effect. The resultant tree structure can be used to explore the overall interaction between treatment and other covariates and help identify and describe possible target populations on which an experimental treatment demonstrates desired efficacy. We follow the standard CART (Breiman, et al., 1984) methodology to develop the interaction tree structure. Variable importance information is extracted via random forests of interaction trees. Both simulated experiments and an analysis of the primary billiary cirrhosis (PBC) data are provided for evaluation and illustration of the proposed procedure.