Everything you need to know about matching adjusted indirect comparisons

An Interview with Daniel Saure

What can we do about indirect comparisons to make it better and more efficient rather than using the usual technique?
What are the indirect comparisons in terms of the efficacy of different drugs?
What experiences have you had when the type of one-to-one approach is better?

In today’s episode, Daniel and I talk about these questions and discuss more the following points:

• Bucher vs MAIC – advantages and disadvantages
• Methodik MAIC
• NICE technical document (http://nicedsu.org.uk/technical-support-documents/population-adjusted-indirect-comparisons-maic-and-stc/) – including R code
• Which baseline variables to include?
• What to do if you have multiple studies on one side?
  • patient-level data meta-analyses
  • literature studies meta-analyses
• How to compute the “average” baseline variables?
• How to adjust for baseline variables?
• What are the different ways to adjust? (https://www.ncbi.nlm.nih.gov/pubmed/30661638)
• How does it relate to network meta-analyses

Reference: Case study IXE vs SECU

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