论文标题

使用临床试验登记处为COPAS选择模型告知荟萃分析中的出版偏差

Using clinical trial registries to inform Copas selection model for publication bias in meta-analysis

论文作者

Huang, Ao, Komukai, Sho, Friede, Tim, Hattori, Satoshi

论文摘要

临床试验登记处的研究方案的预期注册是最大程度地减少荟萃分析中出版偏见的风险,并且如今已提供了一些临床试验注册。但是,它们主要用作搜索研究和提交给注册表的信息的工具,尚未尽可能有效地利用。在解决荟萃分析中的出版物偏见时,使用COPAS选择模型的灵敏度分析是广泛使用的图形方法(例如漏斗图和修剪和填充方法)的更客观的替代方法。尽管具有量化出版偏差的潜在影响的能力,但该模型的缺点是某些参数尚未指定。这可能会导致解释灵敏度分析的结果一些困难。在本文中,我们通过利用来自临床试验注册的信息,为COPAS选择模型提出了另一种推理程序。我们的方法提供了一种简单而准确的方法来估计COPAS选择模型中所有未知参数。一项模拟研究表明,与现有方法相比,我们提出的方法导致偏见和更准确的置信区间。此外,已经重新分配了两个已发表的荟萃分析,以演示如何在实践中实施所提出的方法。

Prospective registration of study protocols in clinical trial registries is a useful way to minimize the risk of publication bias in meta-analysis, and several clinical trial registries are available nowadays. However, they are mainly used as a tool for searching studies and information submitted to the registries has not been utilized as efficiently as it could. In addressing publication bias in meta-analyses, sensitivity analysis with the Copas selection model is a more objective alternative to widely-used graphical methods such as the funnel-plot and the trim-and-fill method. Despite its ability to quantify the potential impact of publication bias, a drawback of the model is that some parameters not to be specified. This may result in some difficulty in interpreting the results of the sensitivity analysis. In this paper, we propose an alternative inference procedure for the Copas selection model by utilizing information from clinical trial registries. Our method provides a simple and accurate way to estimate all unknown parameters in the Copas selection model. A simulation study revealed that our proposed method resulted in smaller biases and more accurate confidence intervals than existing methods. Furthermore, two published meta-analyses had been re-analysed to demonstrate how to implement the proposed method in practice.

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