Fiero Mallorie, Huang Shuang, Bell Melanie L
Division of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona, USA.
BMJ Open. 2015 May 13;5(5):e007378. doi: 10.1136/bmjopen-2014-007378.
Cluster randomised trials (CRTs) randomise participants in groups, rather than as individuals, and are key tools used to assess interventions in health research where treatment contamination is likely or if individual randomisation is not feasible. Missing outcome data can reduce power in trials, including in CRTs, and is a potential source of bias. The current review focuses on evaluating methods used in statistical analysis and handling of missing data with respect to the primary outcome in CRTs.
We will search for CRTs published between August 2013 and July 2014 using PubMed, Web of Science and PsycINFO. We will identify relevant studies by screening titles and abstracts, and examining full-text articles based on our predefined study inclusion criteria. 86 studies will be randomly chosen to be included in our review. Two independent reviewers will collect data from each study using a standardised, prepiloted data extraction template. Our findings will be summarised and presented using descriptive statistics.
This methodological systematic review does not need ethical approval because there are no data used in our study that are linked to individual patient data. After completion of this systematic review, data will be immediately analysed, and findings will be disseminated through a peer-reviewed publication and conference presentation.
整群随机试验(CRTs)将参与者按组进行随机分组,而非个体随机分组,是用于评估健康研究中干预措施的关键工具,这些研究中可能存在治疗污染问题,或者个体随机分组不可行。缺失的结局数据会降低试验效能,包括整群随机试验,并且是潜在的偏倚来源。本综述重点评估整群随机试验中关于主要结局的统计分析和缺失数据处理所使用的方法。
我们将使用PubMed、科学网和PsycINFO检索2013年8月至2014年7月发表的整群随机试验。我们将通过筛选标题和摘要,并根据预先定义的研究纳入标准审查全文文章来识别相关研究。将随机选择86项研究纳入我们的综述。两名独立的评审员将使用标准化的、预先试点的数据提取模板从每项研究中收集数据。我们的研究结果将使用描述性统计进行总结和呈现。
本方法学系统综述无需伦理批准,因为我们的研究中未使用与个体患者数据相关的数据。完成本系统综述后,将立即对数据进行分析,研究结果将通过同行评审出版物和会议报告进行传播。