Lunny Carole, Higgins J P T, White Ian R, Dias Sofia, Hutton B, Wright J M, Veroniki Areti-Angeliki, Whiting P F, Tricco A C
Precision, Vancouver, Canada.
Knowledge Translation Programme, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, ON, Canada.
BMJ. 2025 Mar 18;388:e079839. doi: 10.1136/bmj-2024-079839.
Systematic reviews with network meta-analysis (NMA) have potential biases in their conduct, analysis, and interpretation. If the results or conclusions of an NMA are integrated into policy or practice without any consideration of risks of bias, decisions could unknowingly be based on incorrect results, which could translate to poor patient outcomes. The RoB NMA (Risk of Bias in Network Meta-Analysis) tool answers a clearly defined need for a rigorously developed tool to assess risk of bias in NMAs of healthcare interventions. In this guidance article, we describe and provide a justification for the tool’s 17 items, their mechanism of bias, pertinent examples, and how to assess an NMA based on each response option.
采用网状Meta分析(NMA)的系统评价在实施、分析和解释过程中存在潜在偏倚。如果在未考虑偏倚风险的情况下将NMA的结果或结论纳入政策或实践,决策可能在不知情的情况下基于错误结果做出,这可能导致患者预后不良。网状Meta分析偏倚风险(RoB NMA)工具满足了对严格开发的工具的明确需求,该工具用于评估医疗保健干预措施网状Meta分析中的偏倚风险。在本指导文章中,我们描述了该工具的17个条目、其偏倚机制、相关示例,以及如何根据每个回答选项评估网状Meta分析。