Recommendations for the analysis of individually randomised controlled trials with clustering in one arm - a case of continuous outcomes.
Recommendations for the analysis of individually randomised controlled trials with clustering in one arm - a case of continuous outcomes.
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DOI：
10.1186/s12874-016-0249-5
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发表时间：
2016-11-29
影响因子：
4
通讯作者：
Walters SJ
中科院分区：
文献类型：
--
作者：
Flight L;Allison A;Dimairo M;Lee E;Mandefield L;Walters SJ
在一项由医疗专业人员提供治疗的个体随机对照试验中，治疗的有效性（与任何治疗效果无关）似乎可能取决于医疗专业人员的技能、培训甚至热情。这可能导致由同一医疗专业人员治疗的患者的结局可能聚集，但类似的聚类可能不会发生在对照组中。通过四个案例研究，我们的目的是提供实用的指导和建议，在一个arm. Five的聚类元素在一个单独的随机对照试验的结果分析方法在一个arm. Five的分析结果在文献中确定。这些方法中的一些被应用到四个案例研究完成的随机对照试验，在一个手臂的样本量范围从56到539集群。使用统计软件包R和Stata获得结果，并使用森林图进行总结。每个案例研究的集群内相关系数（ICC）都很小（<0.05），表明对集群分配相关结果的依赖性很小。所有拟合的模型都产生了类似的结果，包括最简单的方法，即忽略所考虑的案例研究的聚类。仅在一个组中建模聚类的部分聚类方法最准确地代表试验设计并提供有效结果。在与所考虑的案例研究类似的情况下，对聚类和非聚类臂之间的齐次方差进行建模是足够的。我们建议将未聚类组中的每个参与者视为单个聚类。这种方法在R和Stata中实现起来很简单，推荐用于分析仅在一个组中进行聚类的试验。然而，所考虑的案例研究具有较小的ICC值，限制了这些结果的普遍性。本文的在线版本（doi：10.1186/s12874-016-0249-5）包含补充材料，可供授权用户使用。
In an individually randomised controlled trial where the treatment is delivered by a health professional it seems likely that the effectiveness of the treatment, independent of any treatment effect, could depend on the skill, training or even enthusiasm of the health professional delivering it. This may then lead to a potential clustering of the outcomes for patients treated by the same health professional, but similar clustering may not occur in the control arm. Using four case studies, we aim to provide practical guidance and recommendations for the analysis of trials with some element of clustering in one arm. Five approaches to the analysis of outcomes from an individually randomised controlled trial with clustering in one arm are identified in the literature. Some of these methods are applied to four case studies of completed randomised controlled trials with clustering in one arm with sample sizes ranging from 56 to 539. Results are obtained using the statistical packages R and Stata and summarised using a forest plot. The intra-cluster correlation coefficient (ICC) for each of the case studies was small (<0.05) indicating little dependence on the outcomes related to cluster allocations. All models fitted produced similar results, including the simplest approach of ignoring clustering for the case studies considered. A partially clustered approach, modelling the clustering in just one arm, most accurately represents the trial design and provides valid results. Modelling homogeneous variances between the clustered and unclustered arm is adequate in scenarios similar to the case studies considered. We recommend treating each participant in the unclustered arm as a single cluster. This approach is simple to implement in R and Stata and is recommended for the analysis of trials with clustering in one arm only. However, the case studies considered had small ICC values, limiting the generalisability of these results. The online version of this article (doi:10.1186/s12874-016-0249-5) contains supplementary material, which is available to authorized users.
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