#45 How to perform better disproportionality analyses – Michele Fusaroli & Eugene van Puijenbroek

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For all its ease and speed, disproportionality analysis can be distorted by many biases, making it easy to misuse and misinterpret. Michele Fusaroli from Uppsala Monitoring Centre and Eugene van Puijenbroek from the Netherlands pharmacovigilance centre Lareb explain why we shouldn’t abuse this powerful but fragile tool.

Tune in to find out:

• Why we should never treat disproportionality signals as verdicts
• How poorly performed analyses affect scientists, regulators and patients
• How to avoid the most common sources of bias 

Want to know more?

• Michele and Eugene’s paper in Drug Safety is a concrete guide to charting and sidestepping the pitfalls of disproportionality analysis.
• In another Drug Safety paper, Michele and colleagues show how directed acyclic graphs (DAGs) can help map and address biases in disproportionality analysis.
• Michele also reviewed the method’s limitations in Uppsala Reports, where he argues that ‘pharmacovigilance must move past crude disproportionality’.
• Last year, Retraction Watch covered the spike in pharmacovigilance studies in the literature and why some journals decided to ban drug safety database papers.
• Previously on Drug Safety Matters, Michele and Daniele Sartori discussed the READUS-PV guidelines for reporting disproportionality analyses.
• In 2016, the IMI PROTECT project published recommendations to improve signal detection practices, especially for quantitative methods like disproportionality analysis.
• UMC’s guidebook on signal detection in small datasets offers step-by-step advice for qualitative methods and manual case review.

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