Advances in the GRADE approach to rate the certainty in estimates from a network meta-analysis

成对比较 确定性 分级(工程) 证据质量 荟萃分析 计算机科学 计量经济学 管理科学 数学 医学 人工智能 经济 工程类 几何学 内科学 土木工程
作者
Romina Brignardello‐Petersen,Ashley Bonner,Paul Alexander,Reed Siemieniuk,Toshi A. Furukawa,Bram Rochwerg,Glen Hazlewood,Waleed Alhazzani,Reem A. Mustafa,M. Hassan Murad,Milo A. Puhan,Holger J. Schünemann,Gordon Guyatt
出处
期刊:Journal of Clinical Epidemiology [Elsevier BV]
卷期号:93: 36-44 被引量:561
标识
DOI:10.1016/j.jclinepi.2017.10.005
摘要

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.
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