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GRADE指南34:使用最低限度情境化方法对不精确性进行评级的更新。

GRADE Guidance 34: update on rating imprecision using a minimally contextualized approach.

作者信息

Zeng Linan, Brignardello-Petersen Romina, Hultcrantz Monica, Mustafa Reem A, Murad Mohammad H, Iorio Alfonso, Traversy Gregory, Akl Elie A, Mayer Martin, Schünemann Holger J, Guyatt Gordon H

机构信息

Pharmacy Department/Evidence-based Pharmacy Centre, West China Second University Hospital, Sichuan University and Key Laboratory of Birth Defects and Related Disease of Women and Children, Ministry of Education, No. 20, Section 3, South Renmin Road, Chengdu 610041, China; Department of Health Research Methods, Evidence and Impact, McMaster University, 1280 Main Street West, Hamilton, L8S 4L8 Ontario, Canada.

Department of Health Research Methods, Evidence and Impact, McMaster University, 1280 Main Street West, Hamilton, L8S 4L8 Ontario, Canada.

出版信息

J Clin Epidemiol. 2022 Oct;150:216-224. doi: 10.1016/j.jclinepi.2022.07.014. Epub 2022 Aug 4.

Abstract

OBJECTIVES

The aim of this study is to provide updated guidance on when The Grading of Recommendations Assessment, Development and Evaluation (GRADE) users should consider rating down more than one level for imprecision using a minimally contextualized approach.

STUDY DESIGN AND SETTING

Based on the first GRADE guidance addressing imprecision rating in 2011, a project group within the GRADE Working Group conducted iterative discussions and presentations at GRADE Working Group meetings to produce this guidance.

RESULTS

GRADE suggests aligning imprecision criterion for systematic reviews and guidelines using the approach that relies on thresholds and confidence intervals (CI) of absolute effects as a primary criterion for imprecision rating (i.e., CI approach). Based on the CI approach, when a CI appreciably crosses the threshold(s) of interest, one should consider rating down two or three levels. When the CI does not cross the threshold(s) and the relative effect is large, one should implement the optimal information size (OIS) approach. If the sample size of the meta-analysis is far less than the OIS, one should consider rating down more than one level for imprecision.

CONCLUSION

GRADE provides updated guidance for imprecision rating in a minimally contextualized approach, with a focus on the circumstances in which one should seriously consider rating down two or three levels for imprecision.

摘要

目标

本研究旨在提供最新指南,以说明推荐意见评估、制定与评价分级(GRADE)的使用者何时应采用最低限度情境化方法,因不精确性而将证据等级下调一级以上。

研究设计与背景

基于2011年首份关于不精确性分级的GRADE指南,GRADE工作组内的一个项目组在GRADE工作组会议上进行了反复讨论和汇报,以制定本指南。

结果

GRADE建议,在系统评价和指南中,采用依赖绝对效应阈值和置信区间(CI)的方法作为不精确性分级的主要标准(即CI方法)来统一不精确性标准。基于CI方法,当CI明显越过感兴趣的阈值时,应考虑将证据等级下调两级或三级。当CI未越过阈值且相对效应较大时,应采用最佳信息规模(OIS)方法。如果荟萃分析的样本量远小于OIS,则应考虑因不精确性将证据等级下调一级以上。

结论

GRADE以最低限度情境化方法提供了关于不精确性分级的最新指南,重点关注应认真考虑因不精确性将证据等级下调两级或三级的情况。

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