Towards a Framework for Case Identification in Pharmacovigilance: Not All Reports are Created Equal

Retrieval of adverse event reports based on coded drug-event co-occurrence enables large-scale pharmacovigilance analyses, but yields candidate reports rather than validated cases, risking misinterpretation if used alone.

Aim

To develop and apply a framework for identification and characterization of clinically meaningful case series in pharmacovigilance.

Methods

We conducted two case studies. The first developed and refined the framework in an information-rich setting, focusing on drug-induced impulsivity across selected drugs; the second tested its applicability in a more routine, information-poor setting, focusing on drug-induced suicidality.

Results

In Case 1, non-relevant reports were frequent for drugs with uncertain evidence and negative controls (≈20-40%) compared to drugs with established causal roles (4%). The emerging framework assessed relevance based on exposure, event, drug-event relationship, and population. For suspected adverse drug reactions, relevant reports were further characterized by reporter suspicion and evidentiary qualifiers supporting or refuting causality; higher suspicion was associated with more supportive qualifiers. Applied to Case 2, the framework ruled out 69% of reports as non-relevant but highlighted substantial non-assessability (17%).

Conclusions

In pharmacovigilance, retrieval is not equivalent to case identification. Relevance is question-specific and shaped by how reports are captured, processed, and retrieved. This can be especially critical for emerging or bias-prone safety questions. Transparent and reproducible case definition and adjudication are essential for interpretable analyses.

Graphical Abstract

Code-based retrieval of drug–event co-occurrence yields a heterogeneous set of candidate reports that does not directly correspond to a clinically meaningful case series. The proposed framework separates case identification from retrieval by adjudicating relevance across exposure, event, relationship, and context, ruling out non-relevant or non-assessable reports. Relevant reports are further qualified by reporter suspicion and evidentiary features, enabling more interpretable pharmacovigilance analyses.