Wu Darong, Akl Elie A, Guyatt Gordon H, Devereaux Philip J, Brignardello-Petersen Romina, Prediger Barbara, Patel Krupesh, Patel Namrata, Lu Taoying, Zhang Yuan, Falavigna Maicon, Santesso Nancy, Mustafa Reem A, Zhou Qi, Briel Matthias, Schünemann Holger J
Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, ON, Canada.
Trials. 2014 Jan 23;15:33. doi: 10.1186/1745-6215-15-33.
Although even randomization (that is, approximately 1:1 randomization ratio in study arms) provides the greatest statistical power, designed uneven randomization (DUR), (for example, 1:2 or 1:3) is used to increase participation rates. Until now, no convincing data exists addressing the impact of DUR on participation rates in trials. The objective of this study is to evaluate the epidemiology and to explore factors associated with DUR.
We will search for reports of RCTs published within two years in 25 general medical journals with the highest impact factor according to the Journal Citation Report (JCR)-2010. Teams of two reviewers will determine eligibility and extract relevant information from eligible RCTs in duplicate and using standardized forms. We will report the prevalence of DUR trials, the reported reasons for using DUR, and perform a linear regression analysis to estimate the association between the randomization ratio and the associated factors, including participation rate, type of informed consent, clinical area, and so on.
A clearer understanding of RCTs with DUR and its association with factors in trials, for example, participation rate, can optimize trial design and may have important implications for both researchers and users of the medical literature.
尽管随机化(即研究组中随机化比例约为1:1)能提供最大的统计效能,但设计不均衡随机化(DUR,例如1:2或1:3)被用于提高参与率。到目前为止,尚无令人信服的数据说明DUR对试验参与率的影响。本研究的目的是评估其流行病学情况,并探索与DUR相关的因素。
我们将在25种根据《期刊引证报告》(JCR)-2010影响因子最高的综合医学期刊中检索两年内发表的随机对照试验(RCT)报告。由两名评审员组成的团队将确定入选标准,并使用标准化表格从符合条件的RCT中重复提取相关信息。我们将报告DUR试验的患病率、使用DUR的报告原因,并进行线性回归分析以估计随机化比例与相关因素之间的关联,这些因素包括参与率、知情同意类型、临床领域等。
更清楚地了解采用DUR的RCT及其与试验中各因素(如参与率)的关联,可优化试验设计,可能对医学文献的研究者和使用者都具有重要意义。