Workshop #8 A primer on indirect and mixed treatment comparison meta-analyses

• Presenters: Dr. George Wells, University of Ottawa Heart Institute; Vijay Shukla and Chris Cameron, Canadian Agency for Drugs and Technologies in Health

Estimating the benefits of competing healthcare interventions is at the core of health technology assessment. It is generally accepted that randomized controlled trials (RCTs) are the most reliable source of information for such assessments. Traditional meta-analysis is a method for combining evidence from multiple RCTs in order to obtain pooled estimates of efficacy.  However, even if traditional meta-analyses are performed perfectly using perfect data, they are limited in that they only provide information on one treatment comparison. Furthermore, head-to-head RCTs may not have been conducted between the treatments of interest. As such, traditional meta-analyses may not address the question of interest of many policy makers and healthcare professionals – which treatment option is best among all available treatments? 

In recent years, different methods have evolved which enable estimates of efficacy of multiple treatments simultaneously or estimates of efficacy in the absence of trials between treatments. The following workshop reviews indirect and mixed treatment comparison (MTC) approaches to evidence synthesis.  This workshop is intended for those wanting to learn more about indirect and MTC meta-analysis in general, how indirect and MTC calculations are actually made, and how indirect and MTC meta-analysis can be used as a tool for health technology assessment. The workshop will include a number of different segments, including a general description of different types of meta-analysis; illustrations on how to quantitatively conduct indirect and MTC meta-analyses; real-world practical policy examples; and how indirect and MTC in general can be useful for researchers, industry, health care professionals and decision-makers.