READUS-PV stands for: REporting of A Disproportionality analysis for drUg Safety signal detection using individual case safety reports in PharmacoVigilance
READUS-PV mainly developed to Standardize the reporting of Disproportionality analysis (DA) used for drug safety signal detection based on individual case safety reports (ICSRs) in pharmacovigilance.
Disproportionality analysis is a signal detection technique widely used in spontaneous reporting systems (such as EudraVigilance, FAERS, VigiBase and industry safety databases) to identify drug-event combinations that occur more frequently than expected. These methods help flag potential safety issues that may not have been detected during clinical trials due to limited sample sizes and controlled settings.
Commonly Used DA Methods Include:
- Proportional Reporting Ratio (PRR)
- Reporting Odds Ratio (ROR)
- Information Component (IC) – Bayesian method used by WHO’s UMC
- Empirical Bayes Geometric Mean (EBGM) – Used by FDA
These techniques compare the observed frequency of a specific adverse event associated with a particular drug against the expected frequency, based on the background reporting of other drugs and events. Although Disproportionality Analyses (DAs) have been instrumental in pharmacovigilance for over two decades, the lack of a structured reporting framework has led to the misinterpretation of critical safety insights and the failure to distinguish between statistical signals and validated risks.
The READUS-PV guidelines were developed by an international consortium of 34 experts in pharmacovigilance, representing a wide range of sectors, including Academia, Pharmaceutical industry, Regulatory authorities (e.g., EMA, national agencies) and Independent safety researchers. The development process followed a modified Delphi consensus method, ensuring rigorous peer input and agreement on the final checklist.
The READUS-PV guidelines provides a checklist-based approach and these guidelines aim to:
- Improve transparency in how DA results are reported
- Enhance reproducibility of analyses across studies and settings
- Enable consistent interpretation of potential safety signals
- Support evidence-based decision-making in regulatory and public health contexts
The checklist mainly comprise of –
14 Main Items (32 Recommendations)
These address the full scope of a disproportionality analysis report, including:
- Objective and context of the analysis
- Case selection criteria (drugs and events)
- Data sources and their limitations
- Choice and justification of comparator/reference groups
- Statistical methodology used (e.g., PRR, ROR, IC, EBGM)
- Handling of bias (confounding, masking)
- Assessment of robustness and sensitivity
- Signal qualification – Making a clear distinction between statistical association and confirmed safety signal
• 4 Abstract-Specific Items (12 Recommendations)
These ensure that the abstract of a publication:
- Accurately reflects the objectives
- Summarizes methods and statistical tools used
- Conveys major findings and limitations
- Clearly states implications or next steps
• Glossary of Terms
To harmonize terminology across studies, a comprehensive glossary accompanies the guidelines, reducing the risk of misinterpretation by readers from diverse backgrounds.
The guidelines were spotlighted at the DIA 2025 Global Annual Meeting, where regulators and industry leaders echoed a common message: standardizing DA reporting is not just a scientific necessity—it’s a regulatory imperative. Organizations such as the EMA, MHRA, and Health Canada are increasingly advocating for READUS-PV-compliant reporting in submissions involving signal detection.
The guidelines are listed on:
- The READUS-PV official website
- The EQUATOR Network
- Peer-reviewed publications such as Frontiers in Pharmacology and Drug Safety