Exploring the complexities of disproportionality analysis in pharmacovigilance: reflections on the READUS-PV guideline and a call to action

The use of disproportionality analysis (DA) in pharmacovigilance to detect signals of disproportionate reporting (SDRs) has gained popularity, resulting in a surge of publications based on aggregate analysis of spontaneously reported adverse events (AE). The recently published READUS-PV guideline, designed to standardize reporting practices of DA-based publications, is a commendable first step toward standardizing DA reporting; however, it will not overcome totally many of the inherent limitations of DA including their inability to eliminate unnecessary noise in order to identify true signals. The limitations arise from the data sources of AEs, the analytic approaches, and the interpretability of the results. This article discusses those limitations, highlights the challenges posed by the premature publication of safety signals derived from spontaneous reports, and evaluates the READUS-PV guideline's potential to improve interpretation of DA results. The article emphasizes that effective reporting of safety signals is only the first step; a broader, coordinated effort is necessary to establish clear scientific boundaries on what aspects of signal detection should be publicly shared to prevent unwarranted alarm and misinterpretation. It proposes the formation of a consortium, or a similar effort, led by regulators and involving academia and industry, to develop standards for the responsible validation and sharing of safety signal data.