16/02/2026
Over the past decades, disproportionality analysis has become the workhorse of signal detection: widely used, well-established, and deeply embedded in regulatory practice.
However, a growing number of published studies use these methods for more than generating new hypotheses, often overlooking the inherent biases within adverse event reporting databases that require careful clinical review and assessment.
In , Michele Fusaroli explores how disproportionality analysis can remain part of the scientific toolbox without losing the precious fruits that only adverse event reports can offer.
Read more at the link below👇
Disproportionality analysis is pharmacovigilance’s signal-detection workhorse. But more reports do not mean better evidence, and crude results can mislead.