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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