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Estimating causal effects using prior information on nontrial treatments

机译:使用关于非审判的先验信息估算因果效应 治疗方法

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摘要

>Background Departures from randomized treatments complicate the analysis of many randomized controlled trials. Intention-to-treat analysis estimates the effect of being allocated to treatment. It is now possible to estimate the effect of receiving treatment without assuming comparability of groups defined by actual treatment. However, the methodology is largely confined to trials where the only treatment changes were switches to other trial treatments.>Purpose To propose a method for comparing the effects of receiving trial treatments in an active-controlled clinical trial where some participants received nontrial treatments and others received no treatment at all, and to illustrate the method in the PENTA 5 trial in HIV-infected children.>Methods We combine the instrumental variables approach, which forms unbiased estimating equations based on the randomization but does not fully identify the contrasts of trial treatment effects, with prior information about the distribution of possible effects of nontrial treatments and of one trial treatment; we do not need to use prior information about the comparisons of trial treatments. Prior information in PENTA 5 was elicited from the investigators.>Results In PENTA 5, the prior information suggested that all treatments were beneficial, but there was uncertainty about the degree of benefit. Allowing for this prior information changed point estimates and increased standard errors compared with ignoring nontrial treatments.>Limitations The method depends on the correct specification of the causal effect of treatment: in PENTA 5, this assumed a linear effect of dose and no interactions between treatments. This specification is hard to check from the data but can be explored in sensitivity analyses. Prior information would be better derived from the literature whenever possible.>Conclusions The use of partial prior information gives a way to adjust for complex patterns of departures from randomized treatments. It should be useful in all trials where nontrial treatments are used and in active-controlled trials where trial treatments are not universally used.
机译:>背景随机治疗的出现使许多随机对照试验的分析变得复杂。意向治疗分析估计了分配给治疗的效果。现在可以估计接受治疗的效果,而无需假设实际治疗定义的组之间具有可比性。但是,该方法学主要限于仅改变治疗方法而又转向其他试验方法的试验。>目的提出一种在主动控制的临床试验中比较接受试验治疗效果的方法,其中有些参与者接受了非审判治疗,而其他参与者则根本没有接受治疗,并说明了PENTA 5试验在感染HIV的儿童中的方法。>方法我们结合了工具变量方法,形成了基于以下因素的无偏估计方程:随机分组,但不能完全识别试验治疗效果的差异,并事先获得有关非试验治疗和一种试验治疗可能影响的分布的信息;我们不需要使用有关比较试验治疗的先验信息。 PENTA 5中的先验信息来自调查人员。>结果在PENTA 5中,先验信息建议 所有的治疗方法都是有益的,但程度尚不确定 受益。考虑到此先验信息,可更改点估算值, 与忽略非审判治疗相比,标准误增加了。>局限性该方法取决于正确的方法 治疗因果关系说明:在PENTA 5中,假设 剂量的线性效应,治疗之间没有相互作用。这个规格 很难从数据中进行检查,但可以在敏感性分析中进行探索。 每当有文献时,最好能从文献中获得先验信息 >结论:使用部分先验信息 提供一种方法来调整与随机偏离的复杂模式 治疗。在使用非试验性治疗的所有试验中都应该有用 以及在主动控制性试验中,治疗方法并不普遍 用过的。

著录项

  • 期刊名称 SAGE Choice
  • 作者

    Simon J Bond; Ian R White;

  • 作者单位
  • 年(卷),期 -1(7),6
  • 年度 -1
  • 页码 664–676
  • 总页数 13
  • 原文格式 PDF
  • 正文语种
  • 中图分类
  • 关键词

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