Department of Health Research Methods, Evidence and Impact, McMaster University, 1280 Main St W, Hamilton, Ontario L8S 4K1, Canada; Evidence Based Dentistry Unit, Faculty of Dentistry, Universidad de Chile, Sergio Livingstone Pohlhammer 943, Independencia, Santiago, Chile.
Department of Health Research Methods, Evidence and Impact, McMaster University, 1280 Main St W, Hamilton, Ontario L8S 4K1, Canada.
J Clin Epidemiol. 2018 Jan;93:36-44. doi: 10.1016/j.jclinepi.2017.10.005. Epub 2017 Oct 17.
This article describes conceptual advances of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) working group guidance to evaluate the certainty of evidence (confidence in evidence, quality of evidence) from network meta-analysis (NMA). Application of the original GRADE guidance, published in 2014, in a number of NMAs has resulted in advances that strengthen its conceptual basis and make the process more efficient. This guidance will be useful for systematic review authors who aim to assess the certainty of all pairwise comparisons from an NMA and who are familiar with the basic concepts of NMA and the traditional GRADE approach for pairwise meta-analysis. Two principles of the original GRADE NMA guidance are that we need to rate the certainty of the evidence for each pairwise comparison within a network separately and that in doing so we need to consider both the direct and indirect evidence. We present, discuss, and illustrate four conceptual advances: (1) consideration of imprecision is not necessary when rating the direct and indirect estimates to inform the rating of NMA estimates, (2) there is no need to rate the indirect evidence when the certainty of the direct evidence is high and the contribution of the direct evidence to the network estimate is at least as great as that of the indirect evidence, (3) we should not trust a statistical test of global incoherence of the network to assess incoherence at the pairwise comparison level, and (4) in the presence of incoherence between direct and indirect evidence, the certainty of the evidence of each estimate can help decide which estimate to believe.
本文描述了 GRADE 工作组指南在评估来自网络荟萃分析（NMA）的证据确定性（证据置信度、证据质量）方面的概念进展。在一些 NMA 中应用原始 GRADE 指南，加强了其概念基础并使过程更高效，从而取得了一些进展。本指南将有助于系统评价作者评估 NMA 中所有两两比较的确定性，并且熟悉 NMA 的基本概念和传统的 GRADE 方法用于两两荟萃分析。原始 GRADE NMA 指南的两个原则是，我们需要分别对网络内的每个两两比较的证据进行评估，并且在这样做时，我们需要考虑直接证据和间接证据。我们提出、讨论并举例说明了四个概念上的进展：（1）在对直接和间接估计进行评级以告知 NMA 估计的评级时，不必考虑不精确性；（2）当直接证据的确定性高且直接证据对网络估计的贡献至少与间接证据一样大时，无需对间接证据进行评级；（3）我们不应该依赖网络整体不协调性的统计检验来评估两两比较水平的不协调性；（4）在直接证据和间接证据之间存在不一致性的情况下，每个估计的证据确定性有助于决定相信哪个估计。
