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.

Keywords: SDR; adverse drug reactions; disproportionality; disproportionality analyses; signal detection; spontaneous reporting database.

FIGURE 1

Flowchart of signal management, simplified and applied to reports of suspected ADRs. For a complete overview of the process, please see Good Vigilance Practices Module IX (European Medicine Agency, 2017). Throughout the phases of signal management, signals are continuously prioritized within signal prioritization. Shape borders in black indicate the steps that are most relevant to signals of disproportionate reporting.