Evaluation of networks of randomized trials
Evaluation of networks of randomized trials
复制标题
DOI：
10.1177/0962280207080643
复制
发表时间：
2008-06-01
影响因子：
2.3
通讯作者：
Ioannidis, John P. A.
中科院分区：
文献类型：
--
作者：
Salanti, Georgia;Higgins, Julian P. T.;Ioannidis, John P. A.
随机试验可以被设计并解释为单一实验，或者也可以在其他类似或相关证据的背景下看待。对于不同的主题，现有随机证据的数量和复杂性各不相同。系统综述可能有助于识别现有随机证据中的空白，指出试验之间的差异，并规划未来的试验。系统综述的一种新颖、有前景但也备受争议的扩展——混合治疗比较（MTC）荟萃分析，最近变得越来越受欢迎。MTC荟萃分析在解释来自试验网络的现有随机证据方面可能有价值，并且能够对许多不同的治疗方法进行排序，而不仅仅局限于简单的两两比较。然而，对网络的评估也带来了特殊的挑战和注意事项。在本文中，我们回顾了MTC荟萃分析的统计方法。我们讨论了不一致性的概念以及为评估它而提出的方法，还有仍然存在的方法学空白。我们引入了网络几何形状和不对称性的概念，并提出了用于评估不对称性的指标。最后，我们讨论了不一致性、网络几何形状和不对称性在为未来试验规划提供信息方面的影响。
Randomized trials may be designed and interpreted as single experiments or they may be seen in the context of other similar or relevant evidence. The amount and complexity of available randomized evidence vary for different topics. Systematic reviews may be useful in identifying gaps in the existing randomized evidence, pointing to discrepancies between trials, and planning future trials. A new, promising, but also very much debated extension of systematic reviews, mixed treatment comparison (MTC) meta-analysis, has become increasingly popular recently. MTC meta-analysis may have value in interpreting the available randomized evidence from networks of trials and can rank many different treatments, going beyond focusing on simple pairwise-comparisons. Nevertheless, the evaluation of networks also presents special challenges and caveats. In this article, we review the statistical methodology for MTC meta-analysis. We discuss the concept of inconsistency and methods that have been proposed to evaluate it as well as the methodological gaps that remain. We introduce the concepts of network geometry and asymmetry, and propose metrics for the evaluation of the asymmetry. Finally, we discuss the implications of inconsistency, network geometry and asymmetry in informing the planning of future trials.