Disproportionality analyses are a mainstay of pharmacovigilance research, but without clear guidelines, they often lead to confusion and misinterpretation. Enter the READUS-PV statement: the first-ever guide for reporting disproportionality analyses that are replicable, reliable, and reproducible.

Tune in to find out:

The history of reporting guidelines in pharmacovigilance and why the READUS-PV guidelines were created
Why there has been a spike in the publication of disproportionality analyses in recent years and what this means for their reliability
What it means to publish “good” pharmacovigilance science

Want to know more?

Read the READUS-PV guidelines, why they were created, and why they are important.
In 2021, Khouri and colleagues showed that current methods and models used for disproportionality analyses are unreliable, and Mouffak and colleagues found that there is a tendency to overstate results in published disproportionality analyses.
A book on data mining techniques in Pharmacovigilance by Poluzzi and colleagues delves deeper into this exponential increase in disproportionality analyses.
This paper elaborates on the Delphi technique, and how it is used to gather data from reviewers to achieve scientific consensus on a problem.

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#31 A guide to reporting disproportional...