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Network Meta-Analyses: Much more than a press-the-button exercise

Network Meta-Analyses: Much more than a press-the-button exercise

FromThe Effective Statistician - in association with PSI


Network Meta-Analyses: Much more than a press-the-button exercise

FromThe Effective Statistician - in association with PSI

ratings:
Length:
25 minutes
Released:
Jul 19, 2022
Format:
Podcast episode

Description

What can go wrong with network meta-analyses?

You often have multiple endpoints but these are not collected consistently across all the studies included in the NMA. How do you deal with this?


Even with the same variables assessed over studies, they might be collected at different time points. This often has an effect on both efficacy and safety results. What do you do?

Your placebo treatment might change over time and consequently your placebo response. Often placebo plays a crucial part in your network, but can you really pool all your placebo arms? The patient population differs between studies and hence between treatments. How do you control this bias?

The pool of relevant treatments differs across countries when using network meta-analyses for HTA submissions. Should you adapt your NMA for each country's submission?

You’re not submitting all your HTA dossiers at once and thus the literature search needs to be updated repeatedly hence you input data into the NMA. How big are the differences and how long will it take to update everything (and what will it cost?)?
Released:
Jul 19, 2022
Format:
Podcast episode

Titles in the series (100)

The podcast from statisticians for statisticians to have a bigger impact at work. This podcast is set up in association with PSI - Promoting Statistical Insight. This podcast helps you to grow your leadership skills, learn about ongoing discussions in the scientific community, build you knowledge about the health sector and be more efficient at work. This podcast helps statisticians at all levels with and without management experience. It is targeted towards the health, but lots of topics will be important for the wider data scientists community.