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, the presenters 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. The tool is available here.
Presenter Bios
Dr. Areti Angeliki Veroniki is an Associate Professor at the Center for Evidence Synthesis in Health (CESH), Department of Health Services, Policy, and Practice, School of Public Health, Brown University, Providence, Rhode Island, USA. She is co-chair of the Methods Executive and co-convenor of the Statistical Methods Group in Cochrane. Her research interests are in optimizing the processes of evidence-based medicine, and in the statistical modeling for evidence synthesis, including network meta-analysis.
Dr. Carole Lunny is a Senior Research Scientist, HEOR division of Precision AQ and an affiliated methodologist with the Cochrane Hypertension Review Group, and the Therapeutics Initiative at the University of British Columbia. Dr Lunny completed her PhD in clinical epidemiologist with Cochrane Australia. You can access her publication here.
