Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; NIHR Bristol Evidence Synthesis Group, University of Bristol, Bristol, UK; NIHR Applied Research Collaboration West (ARC West) at University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK.
Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada.
Environ Int. 2024 Apr;186:108602. doi: 10.1016/j.envint.2024.108602. Epub 2024 Mar 24.
Observational epidemiologic studies provide critical data for the evaluation of the potential effects of environmental, occupational and behavioural exposures on human health. Systematic reviews of these studies play a key role in informing policy and practice. Systematic reviews should incorporate assessments of the risk of bias in results of the included studies.
To develop a new tool, Risk Of Bias In Non-randomized Studies - of Exposures (ROBINS-E) to assess risk of bias in estimates from cohort studies of the causal effect of an exposure on an outcome.
ROBINS-E was developed by a large group of researchers from diverse research and public health disciplines through a series of working groups, in-person meetings and pilot testing phases. The tool aims to assess the risk of bias in a specific result (exposure effect estimate) from an individual observational study that examines the effect of an exposure on an outcome. A series of preliminary considerations informs the core ROBINS-E assessment, including details of the result being assessed and the causal effect being estimated. The assessment addresses bias within seven domains, through a series of 'signalling questions'. Domain-level judgements about risk of bias are derived from the answers to these questions, then combined to produce an overall risk of bias judgement for the result, together with judgements about the direction of bias.
ROBINS-E provides a standardized framework for examining potential biases in results from cohort studies. Future work will produce variants of the tool for other epidemiologic study designs (e.g. case-control studies). We believe that ROBINS-E represents an important development in the integration of exposure assessment, evidence synthesis and causal inference.
观察性流行病学研究为评估环境、职业和行为暴露对人类健康的潜在影响提供了关键数据。对这些研究进行系统评价在为政策和实践提供信息方面发挥着关键作用。系统评价应纳入对纳入研究结果偏倚风险的评估。
开发一种新工具,即暴露的非随机研究偏倚风险评估工具(ROBINS-E),以评估暴露对结局的因果效应的队列研究中估计值的偏倚风险。
ROBINS-E 是由来自不同研究和公共卫生学科的大量研究人员通过一系列工作组、现场会议和试点测试阶段开发的。该工具旨在评估评估暴露对结局的影响的特定结果(暴露效应估计值)的个体观察性研究中的偏倚风险。一系列初步考虑因素为核心 ROBINS-E 评估提供了信息,包括正在评估的结果和正在估计的因果效应的详细信息。评估通过一系列“信号问题”针对七个领域的偏倚进行评估。域级偏倚风险判断是根据这些问题的答案得出的,然后将这些判断结合起来,为结果生成总体偏倚风险判断,并对偏倚方向进行判断。
ROBINS-E 为检查队列研究结果中的潜在偏倚提供了一个标准化框架。未来的工作将为其他流行病学研究设计(例如病例对照研究)生成该工具的变体。我们相信,ROBINS-E 代表了暴露评估、证据综合和因果推断综合的重要发展。