Office of Disease Prevention, National Institutes of Health, North Bethesda, MD, USA.
Clin Trials. 2022 Aug;19(4):353-362. doi: 10.1177/17407745211063423. Epub 2022 Jan 6.
This article identifies the most influential methods reports for group-randomized trials and related designs published through 2020. Many interventions are delivered to participants in real or virtual groups or in groups defined by a shared interventionist so that there is an expectation for positive correlation among observations taken on participants in the same group. These interventions are typically evaluated using a group- or cluster-randomized trial, an individually randomized group treatment trial, or a stepped wedge group- or cluster-randomized trial. These trials face methodological issues beyond those encountered in the more familiar individually randomized controlled trial.
PubMed was searched to identify candidate methods reports; that search was supplemented by reports known to the author. Candidate reports were reviewed by the author to include only those focused on the designs of interest. Citation counts and the relative citation ratio, a new bibliometric tool developed at the National Institutes of Health, were used to identify influential reports. The relative citation ratio measures influence at the article level by comparing the citation rate of the reference article to the citation rates of the articles cited by other articles that also cite the reference article.
In total, 1043 reports were identified that were published through 2020. However, 55 were deemed to be the most influential based on their relative citation ratio or their citation count using criteria specific to each of the three designs, with 32 group-randomized trial reports, 7 individually randomized group treatment trial reports, and 16 stepped wedge group-randomized trial reports. Many of the influential reports were early publications that drew attention to the issues that distinguish these designs from the more familiar individually randomized controlled trial. Others were textbooks that covered a wide range of issues for these designs. Others were "first reports" on analytic methods appropriate for a specific type of data (e.g. binary data, ordinal data), for features commonly encountered in these studies (e.g. unequal cluster size, attrition), or for important variations in study design (e.g. repeated measures, cohort versus cross-section). Many presented methods for sample size calculations. Others described how these designs could be applied to a new area (e.g. dissemination and implementation research). Among the reports with the highest relative citation ratios were the CONSORT statements for each design.
Collectively, the influential reports address topics of great interest to investigators who might consider using one of these designs and need guidance on selecting the most appropriate design for their research question and on the best methods for design, analysis, and sample size.
本文确定了截至 2020 年发表的最有影响力的群组随机试验和相关设计方法报告。许多干预措施是在真实或虚拟组中或在由共同干预者定义的组中提供给参与者的，因此人们期望对同一组中的参与者进行的观察存在正相关。这些干预措施通常使用群组或聚类随机试验、个体随机分组治疗试验或逐步楔形群组或聚类随机试验进行评估。这些试验面临着超出更熟悉的个体随机对照试验的方法问题。
在 PubMed 中搜索候选方法报告；该搜索由作者已知的报告补充。作者对候选报告进行了审查，仅包括那些专注于感兴趣设计的报告。引用计数和相对引用比，一种在国立卫生研究院开发的新的文献计量工具，用于识别有影响力的报告。相对引用比通过将参考文章的引用率与其他引用参考文章的文章的引用率进行比较，在文章层面上衡量影响力。
总共确定了 1043 篇报告，这些报告发表于 2020 年之前。然而，根据相对引用比或每个设计的特定标准的引用计数，有 55 篇被认为是最有影响力的，其中包括 32 篇群组随机试验报告、7 篇个体随机分组治疗试验报告和 16 篇逐步楔形群组随机试验报告。许多有影响力的报告都是早期出版物，它们引起了人们对这些设计与更熟悉的个体随机对照试验的区别的关注。其他报告是涵盖这些设计广泛问题的教科书。还有一些是针对特定类型数据（例如二项数据、有序数据）、这些研究中常见的特征（例如不等的聚类大小、流失）或研究设计的重要变化（例如重复测量、队列与横断面）的分析方法的“首次报告”。许多报告介绍了样本量计算方法。其他报告描述了如何将这些设计应用于新领域（例如传播和实施研究）。在相对引用比最高的报告中，有每个设计的 CONSORT 声明。
总的来说，这些有影响力的报告涉及到那些可能考虑使用这些设计之一的研究人员非常感兴趣的主题，并需要有关为他们的研究问题选择最合适的设计以及最佳设计、分析和样本量计算方法的指导。
