Everything you need to know about matching adjusted indirect comparisons
- Author
- Alexander Schacht and Benjamin Piske, biometricians, statisticians and leaders in the pharma industry
- Published
- Tue 04 Aug 2020
- Episode Link
- https://podcastae8fac.podigee.io/133-everything-you-need-to-know-about-matching-adjusted-indirect-comparisons
An Interview with Daniel Saure
In today's episode, Daniel and I talk about these questions and discuss more about 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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