School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, UK.
Amgen Ltd, Global Biostatistical Science, 240 Cambridge Science Park, Milton Road, Cambridge, Cambridgeshire, UK.
Res Synth Methods. 2018 Jun;9(2):148-162. doi: 10.1002/jrsm.1278. Epub 2017 Dec 17.
A network meta-analysis allows a simultaneous comparison between treatments evaluated in randomised controlled trials that share at least one treatment with at least one other study. Estimates of treatment effects may be required for treatments across disconnected networks of evidence, which requires a different statistical approach and modelling assumptions to account for imbalances in prognostic variables and treatment effect modifiers between studies. In this paper, we review and discuss methods for comparing treatments evaluated in studies that form disconnected networks of evidence. Several methods have been proposed but assessing which are appropriate often depends on the clinical context as well as the availability of data. Most methods account for sampling variation but do not always account for others sources of uncertainty. We suggest that further research is required to assess the properties of methods and the use of approaches that allow the incorporation of external information to reflect parameter and structural uncertainty.
网络荟萃分析允许对至少与另一项研究共享一种治疗方法的随机对照试验中评估的治疗方法进行同时比较。可能需要对证据不连贯的网络中的治疗方法进行治疗效果估计，这需要采用不同的统计方法和建模假设来考虑研究之间的预后变量和治疗效果修饰剂之间的不平衡。在本文中，我们回顾并讨论了用于比较形成不连贯证据网络的研究中评估的治疗方法的方法。已经提出了几种方法，但评估哪种方法合适通常取决于临床背景以及数据的可用性。大多数方法都考虑了抽样变异性，但并不总是考虑其他不确定性来源。我们建议需要进一步研究以评估方法的特性以及使用允许纳入外部信息以反映参数和结构不确定性的方法。
