GRADE approach to rate the certainty from a network meta-analysis: addressing incoherence
GRADE approach to rate the certainty from a network meta-analysis: addressing incoherence
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DOI：
10.1016/j.jclinepi.2018.11.025
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发表时间：
2019-04-01
影响因子：
7.2
通讯作者：
Guyatt, Gordon H.
中科院分区：
文献类型：
--
作者：
Brignardello-Petersen, Romina;Mustafa, Reem A.;Guyatt, Gordon H.
本文介绍了来自建议评估、开发和评价（GRADE）工作组的官方指导，该工作组指导如何在评估网络荟萃分析证据的确定性时解决不一致性问题。不一致性代表了直接和间接估计之间的重要差异，有助于网络估计。由于研究设计的局限性或发表偏倚、间接性和不传递性而导致的偏倚可能是不连贯的原因。解决不一致性需要判断对网络估计的影响的重要性。审稿人需要警惕的可能性，误导达到过低的评级的确定性，评级下降的不连贯性和其他密切相关的GRADE领域。本文描述并举例说明了其中的每一个问题，并就如何处理这些问题提供了明确的指导。(C)2018爱思唯尔公司All rights reserved.
This article presents official guidance from the Grading of Recommendations Assessments, Development, and Evaluation (GRADE) working group on how to address incoherence when assessing the certainty in the evidence from network meta-analysis. Incoherence represents important differences between direct and indirect estimates that contribute to a network estimate. Bias due to limitations in study design or publication bias, indirectness, and intransitivity may be responsible for incoherence. Addressing incoherence requires a judgment regarding the importance of the impact on the network estimate. Reviewers need to be alert to the possibility of misguidedly arriving at excessively low ratings of certainty by rating down for both incoherence and other closely related GRADE domains. This article describes and illustrates each of these issues and provides explicit guidance on how to deal with them. (C) 2018 Elsevier Inc. All rights reserved.