Interpreting results of network meta-analyses: the GRADE minimally contextualized approach


The GRADE working group has developed a new approach to rating treatments in network meta-analyses that involve more than a handful of interventions. The approach is far superior to those previously suggested in that it takes into account certainty of evidence and precision of estimates. This approach was described in this Cochrane Learning Live webinar.

The topic is of particular interest to anyone involved in creating network meta-analyses. It is also of interest to those who wish to understand how interventions are rated in the context of NMA. 

The session was delivered in July 2022 and below you will find the videos from the webinar, together with accompanying slides to download [PDF].

Part 1: A brief introduction to GRADE approach and network meta-analysis
Part 2: Sucra - yes or no?
Part 3: GRADE's minimally contextualized approach


Presenter Bio

Dr. Gordon Guyatt is a Distinguished Professor, Department of Health Research Methods, Evidence, and Impact, McMaster University, Canada. He played a major role in the development and evolution of the GRADE approach to rating certainty of evidence and strength of recommendations and has played a major role in developing GRADE approaches to network meta-analysis.


Part 1: A brief introduction to GRADE approach and network meta-analysis


Part 2: Sucra – yes or no?


Part 3: GRADE's minimally contextualized approach


Additional materials

Download the slides from the webinar [PDF]