随机对照试验
混淆
医学
指南
公制(单位)
心理干预
系统回顾
循证实践
梅德林
物理疗法
心理学
替代医学
外科
运营管理
精神科
病理
经济
政治学
法学
作者
Holger J. Schünemann,Carlos A. Cuello‐García,Elie A. Akl,Reem A. Mustafa,Joerg J Meerpohl,Kris Thayer,Rebecca L. Morgan,Gerald Gartlehner,Regina Kunz,Srinivasa Vittal Katikireddi,Jonathan A C Sterne,Julian P. T. Higgins,Gordon Guyatt
标识
DOI:10.1016/j.jclinepi.2018.01.012
摘要
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.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.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.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.
科研通智能强力驱动
Strongly Powered by AbleSci AI