Conducting and interpreting disproportionality analyses derived from spontaneous reporting systems

Abstract

Spontaneous reporting systems remain pivotal for post-marketing surveillance and disproportionality analysis (DA) represents a recognized approach for early signal detection. Although DAs cannot be used per se as a standalone approach to assess a drug-related risk and cannot replace clinical judgment in the individual patient, their role remain irreplaceable for rapid detection of rare and unpredictable adverse drug reactions with strong drug-attributable component (e.g., designated medical events), especially when developed by a multidisciplinary team and combined with a careful case-by-case analysis (individual inspection of reports for causality assessment or to uncover reporting patterns and clinical features). In the recent past, a remarkable increase in publications of pharmacovigilance studies using DAs was observed, albeit the quality was debated: several publications contained “spin”, namely, misinterpretation of results to infer causality, calculate incidence, or provide risk stratification, which may ultimately result in unjustified alarm. The development of dedicated Guidelines by the international READUS-PV project (https://readus-statement.org/) will allow reproducible and transparent publication of accurate DAs, thus supporting their real transferability and exploitation by regulators and clinicians. This review offered a perspective on methodological aspects (and understanding) of DAs, their rationale, design, reporting, and interpretation.