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具有连续结局的群组随机交叉试验的最优设计:在固定数量的群组或固定预算下,最佳的时间段和治疗转换数量。

Optimal design of cluster randomized crossover trials with a continuous outcome: Optimal number of time periods and treatment switches under a fixed number of clusters or fixed budget.

机构信息

Department of Methodology and Statistics, Utrecht University, PO Box 80140, Utrecht, TC, 3508, The Netherlands.

出版信息

Behav Res Methods. 2024 Dec;56(8):8820-8830. doi: 10.3758/s13428-024-02505-1. Epub 2024 Sep 13.

DOI:10.3758/s13428-024-02505-1
PMID:39271634
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11525278/
Abstract

In the cluster randomized crossover trial, a sequence of treatment conditions, rather than just one treatment condition, is assigned to each cluster. This contribution studies the optimal number of time periods in studies with a treatment switch at the end of each time period, and the optimal number of treatment switches in a trial with a fixed number of time periods. This is done for trials with a fixed number of clusters, and for trials in which the costs per cluster, subject, and treatment switch are taken into account using a budgetary constraint. The focus is on trials with a cross-sectional design where a continuous outcome variable is measured at the end of each time period. An exponential decay correlation structure is used to model dependencies among subjects within the same cluster. A linear multilevel mixed model is used to estimate the treatment effect and its associated variance. The optimal design minimizes this variance. Matrix algebra is used to identify the optimal design and other highly efficient designs. For a fixed number of clusters, a design with the maximum number of time periods is optimal and treatment switches should occur at each time period. However, when a budgetary constraint is taken into account, the optimal design may have fewer time periods and fewer treatment switches. The Shiny app was developed to facilitate the use of the methodology in this contribution.

摘要

在集群随机交叉试验中,每个集群都被分配了一系列的处理条件,而不仅仅是一种处理条件。这项研究探讨了在每个时间周期结束时进行治疗切换的研究中最佳的时间周期数,以及在固定时间周期数的试验中最佳的治疗切换次数。这是针对具有固定数量集群的试验以及考虑到每个集群、受试者和治疗切换的成本使用预算限制的试验进行的。本研究的重点是具有横向设计的试验,其中在每个时间周期结束时测量连续的结果变量。使用指数衰减相关结构来模拟同一集群内受试者之间的依赖性。使用线性多层混合模型来估计处理效果及其相关方差。最优设计最小化了该方差。使用矩阵代数来确定最优设计和其他高效设计。对于固定数量的集群,具有最大时间周期数的设计是最优的,并且应该在每个时间周期进行治疗切换。然而,当考虑到预算限制时,最优设计可能具有较少的时间周期和较少的治疗切换。开发了 Shiny 应用程序,以方便在本研究中使用该方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbf3/11525278/e254db027328/13428_2024_2505_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbf3/11525278/2dc29d3fd7eb/13428_2024_2505_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbf3/11525278/1a27f713775a/13428_2024_2505_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbf3/11525278/6f17695bb53e/13428_2024_2505_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbf3/11525278/e254db027328/13428_2024_2505_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbf3/11525278/2dc29d3fd7eb/13428_2024_2505_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbf3/11525278/1a27f713775a/13428_2024_2505_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbf3/11525278/6f17695bb53e/13428_2024_2505_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbf3/11525278/e254db027328/13428_2024_2505_Fig4_HTML.jpg

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