Pharmacovigilance can detect unusual drug–event reporting patterns long before their clinical meaning is settled. The interpretive error is to treat signal strength, exposed-population risk, excess above expected occurrence, temporal plausibility, and causal credibility as though they were interchangeable quantities. They are not. Exposure denominators may be incomplete or misclassified; background event rates vary across populations, databases, phenotypes, and calendar periods; and the meaning of an observed excess depends on whether follow-up corresponds to a biologically credible risk period. Treatment switching, discontinuation, indication, and other time-dependent processes further complicate inference. Case-level dechallenge, rechallenge, and temporal coherence can strengthen or weaken an interpretation but cannot independently settle causality. This Current Opinion argues that drug safety signals should be interpreted through an explicitly proposed reconciliation of exposure credibility, background-event compatibility, biologically relevant time, dynamic treatment state, competing explanations, and case chronology. The framework is intended as a qualitative triage architecture, not a validated causality algorithm, prediction model, or regulatory standard.
IJPRAS
