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在具有不完全个体内设计和异质成本和方差的试验中,最优安慰剂治疗比较。

Optimal placebo-treatment comparisons in trials with an incomplete within-subject design and heterogeneous costs and variances.

机构信息

Department of Methodology and Statistics, Utrecht University, Utrecht, The Netherlands.

出版信息

PLoS One. 2023 Apr 20;18(4):e0283382. doi: 10.1371/journal.pone.0283382. eCollection 2023.

Abstract

The aim of a clinical trial is to compare placebo to one or more treatments. The within-subject design is known to be more efficient than the between-subject design. However, in some trials that implement a within-subject design it is not possible to evaluate the placebo and all treatments within each subject. The design then becomes an incomplete within-subject design. An important question is how many subjects should be allocated to each combination of placebo and treatments. This paper studies optimal allocations of subjects in trials with a placebo and two treatments under heterogenous costs and variances. Two optimality criteria that consider the placebo-treatment contrasts simultaneously are considered, and the design is derived under a budgetary constraint. More subjects are allocated to those combinations with higher variances and lower costs. The optimal allocation is compared to the uniform allocation, which allocates equal number of subjects to each placebo and treatment combination, and to the complete within-subject design, where placebo and all treatments are available in each subject. The methodology is illustrated on the basis of an example on consultation time in primary care. A Shiny app is available to facilitate use of the methodology.

摘要

临床试验的目的是将安慰剂与一种或多种治疗方法进行比较。众所周知,与个体间设计相比,个体内设计更为有效。然而,在一些采用个体内设计的试验中,无法在每个个体内评估安慰剂和所有治疗方法。此时,该设计就变成了不完全的个体内设计。一个重要的问题是,对于安慰剂和两种治疗方法的每种组合,应该分配多少个受试者。本文研究了在成本和方差异质的情况下,具有安慰剂和两种治疗方法的试验中的最佳受试者分配。考虑了同时考虑安慰剂-治疗对比的两个最优性标准,并在预算约束下推导出设计。更多的受试者被分配给方差较高、成本较低的组合。将最优分配与均等分配(即每个安慰剂和治疗组合分配相同数量的受试者)和完全个体内设计(即每个受试者都可以使用安慰剂和所有治疗方法)进行了比较。该方法基于初级保健咨询时间的一个例子进行了说明。还提供了一个 Shiny 应用程序来方便使用该方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cbd0/10118159/3cad99816a67/pone.0283382.g001.jpg

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