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GRADE 指南:18. ROBINS-I 及其他评估非随机研究偏倚风险的工具应如何用于评估证据体的确定性。

GRADE guidelines: 18. How ROBINS-I and other tools to assess risk of bias in nonrandomized studies should be used to rate the certainty of a body of evidence.

机构信息

Department of Health Research Methods, Evidence, and Impact and McGRADE Center, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S4K1, Canada; Department of Medicine, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S4K1, Canada.

Department of Health Research Methods, Evidence, and Impact and McGRADE Center, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S4K1, Canada.

出版信息

J Clin Epidemiol. 2019 Jul;111:105-114. doi: 10.1016/j.jclinepi.2018.01.012. Epub 2018 Feb 9.


DOI:10.1016/j.jclinepi.2018.01.012
PMID:29432858
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6692166/
Abstract

OBJECTIVE: To provide guidance on how systematic review authors, guideline developers, and health technology assessment practitioners should approach the use of the risk of bias in nonrandomized studies of interventions (ROBINS-I) tool as a part of GRADE's certainty rating process. STUDY DESIGN AND SETTING: The study design and setting comprised iterative discussions, testing in systematic reviews, and presentation at GRADE working group meetings with feedback from the GRADE working group. RESULTS: We describe where to start the initial assessment of a body of evidence with the use of ROBINS-I and where one would anticipate the final rating would end up. The GRADE accounted for issues that mitigate concerns about confounding and selection bias by introducing the upgrading domains: large effects, dose-effect relations, and when plausible residual confounders or other biases increase certainty. They will need to be considered in an assessment of a body of evidence when using ROBINS-I. CONCLUSIONS: The use of ROBINS-I in GRADE assessments may allow for a better comparison of evidence from randomized controlled trials (RCTs) and nonrandomized studies (NRSs) because they are placed on a common metric for risk of bias. Challenges remain, including appropriate presentation of evidence from RCTs and NRSs for decision-making and how to optimally integrate RCTs and NRSs in an evidence assessment.

摘要

目的:为系统评价作者、指南制定者和卫生技术评估从业者提供指导,说明应如何将非随机干预研究中的偏倚风险(ROBINS-I)工具作为 GRADE 确定性评级过程的一部分加以应用。

研究设计和环境:该研究设计和环境包括迭代讨论、系统评价中的测试以及在 GRADE 工作组会议上的演示,并收到了 GRADE 工作组的反馈。

结果:我们描述了如何使用 ROBINS-I 开始对证据体进行初步评估,以及预期最终评级将在哪里结束。GRADE 通过引入以下升级领域来考虑减轻混杂和选择偏倚问题的因素:效应幅度大、剂量-效应关系以及当合理的残余混杂因素或其他偏倚增加确定性时。在使用 ROBINS-I 进行证据体评估时,需要考虑这些因素。

结论:在 GRADE 评估中使用 ROBINS-I 可能允许更好地比较随机对照试验(RCT)和非随机研究(NRS)的证据,因为它们在偏倚风险的共同度量标准上进行了比较。仍然存在挑战,包括为决策提供 RCT 和 NRS 的证据的适当呈现,以及如何在证据评估中最佳地整合 RCT 和 NRS。

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本文引用的文献

[1]
GRADE guidelines 17: assessing the risk of bias associated with missing participant outcome data in a body of evidence.

J Clin Epidemiol. 2017-7

[2]
The GRADE Working Group clarifies the construct of certainty of evidence.

J Clin Epidemiol. 2017-7

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Annu Rev Public Health. 2017-3-20

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J Clin Epidemiol. 2016-8

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Environ Int. 2016

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BMJ. 2015-3-16

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