Make the “Which, when, and why?” of Bucher vs Bayesian analyses less of a mystery
Bucher vs. Bayesian Indirect Treatment Comparisons (ITCs) - They're Different (Aren't They?)
"So, is this new treatment any better than anything else?" Too often, attempts to answer this crucial (but deceptively simple) question must overcome a major hurdle — the lack of direct head-to-head comparisons with established treatments and emerging competitors. This helps explain why statistical techniques that connect studies of the treatments of interest through evidence networks now have a dominant role in the assessment of comparative effectiveness and safety. In particular, two such methods of indirect treatment comparison (ITC) — Bucher and Bayesian analyses — are widely applied, for example, in the generation of comparative evidence to inform reimbursement submissions. While the availability of these two distinct approaches can offer choice and flexibility (e.g., in meeting varying requirements across different health technology assessment [HTA] bodies), it also, ironically, raises questions about how Bucher and Bayesian analyses themselves compare in situations where either could be used.
 
This webinar explores how Bucher and Bayesian indirect comparisons differ (or not) in evidence networks without closed loops, using side-by-side examples. Specifically, we probe and explain the potential for differences (and similarities) between the approaches across a wide array of factors, including:
  • Type of effect (e.g., hazard ratios vs. mean-differences vs. odds-ratios)
  • Number of studies per comparison
  • Fixed- vs. random-effects models
  • Amount of observed statistical heterogeneity
The ultimate aim is to make the "Which, when, and why?" of Bucher vs. Bayesian analyses much less of a mystery.
 
Featured Presenter
Kyle R. Fahrbach, PhD
Kyle R. Fahrbach, PhD
Principal Statistician, Meta Research
Evidera
Key Learning Objectives
Understand and be able to summarize key methodological principles of Bucher and Bayesian analyses
Learn the expected differences between Bucher and Bayesian results across a variety of combinations of factors
Gain insights into the challenges of deciding between fixed-effects and random-effects models for Bucher vs. Bayesian ITCs
 
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Related Resources
 
Fact Sheet: Meta Research
Read More

 
White Paper: How Similar is "Similar"? A Deeper Dive into Bucher Versus Bayesian Network Meta-Analysis
Read More
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