ipcwswitch: An R package for inverse probability of censoring weighting with an application to switches in clinical trials
ipcwswitch: An R package for inverse probability of censoring weighting with an application to switches in clinical trials
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DOI：
10.1016/j.compbiomed.2019.103339
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发表时间：
2019-08-01
影响因子：
7.7
通讯作者：
Chevret, Sylvie
中科院分区：
文献类型：
--
作者：
Graffeo, Nathalie;Latouche, Aurelien;Chevret, Sylvie
在随机临床试验(RCT)中，分析基于意向治疗原则，以避免组组成中的任何选择偏差。然而，当显著的交叉发生时，由于随机分组的分离丢失，对总体生存的估计可能是有偏差的。为了处理这些切换，人们提出了截尾概率逆加权(IPCW)方法，但它在随机CT中的应用仍然很少，特别是因为它的实现复杂。特别是，对于到事件发生的时间结果，格式化数据可能很困难，特别是当必须管理与时间相关的协变量时，患者之间的测量时间不同。本文旨在介绍R包ipcwSwitch，对在所有患者都将继续接受随机治疗的假设情况下分析治疗对生存的影响具有一定的指导意义。在简要回顾了IPCW方法的主要原则之后，使用玩具示例描述了实施的每个步骤。这些指南在一个旨在评估基于肿瘤分子图谱的晚期癌症治疗益处的案例研究中得到了说明，SHIVA01。
In randomized clinical trials (RCT), the analysis is based on the intent-to-treat principle to avoid any selection bias in the constitution of groups. However, estimates of overall survival can be biased when significant crossover occurs because the separation of randomized groups is lost. To handle these switches, the inverse probability of censoring weighting (IPCW) method has been proposed; however, it is still poorly used in RCT, notably because of its complex implementation. In particular, for time-to-event outcomes, it can be difficult to format data, especially when time-dependent covariates have to be managed, with different measurement times between patients. This paper aims to present the R package ipcwswitch with some guidance for the analysis of the treatment effect on survival in a hypothetical setting where all patients would have continued to take the randomization treatment. After a brief recall of the key principles of the IPCW method, each step of the implementation is described using a toy example. The guidelines are illustrated in a case study that aimed at evaluating the benefit of therapy based on tumour molecular profiling for advanced cancers, SHIVA01.