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Defining 'signal' and its subtypes in pharmacovigilance based on a systematic review of previous definitions
Manfred Hauben1, Jeffrey K Aronson
1Department of Risk Management Strategy, Pfizer Inc., New York, New York 10017, USA. Manfred.Hauben@Pfizer.com
Abstract:
Having surveyed the etymology and previous definitions of the pharmacovigilance term 'signal', we propose a definition that embraces all the surveyed ideas, reflects real-world pharmacovigilance processes, and accommodates signals of both harmful and beneficial effects. The essential definitional features of a pharmacovigilance signal are (i) that it is based on one or more reports of an association between an intervention or interventions and an event or set of related events (e.g. a syndrome), including any type of evidence (clinical or experimental); (ii) that it represents an association that is new and important and has not been previously investigated and refuted; (iii) that it incites to action (verification and remedial action); (iv) that it does not encompass intervention-event associations that are not related to causality or risk with a specified degree of likelihood and scientific plausibility. Based on these features, we propose this definition of a signal of suspected causality: "information that arises from one or multiple sources (including observations and experiments), which suggests a new potentially causal association, or a new aspect of a known association, between an intervention and an event or set of related events, either adverse or beneficial, which would command regulatory, societal or clinical attention, and is judged to be of sufficient likelihood to justify verifiable and, when necessary, remedial actions." This defines an unverified signal; we have also defined term-- indeterminate, verified, and refuted signals--that qualify it in relation to verification. This definition and its accompanying flowchart should inform decision making in considering benefits and harms caused by pharmacological and nonpharmacological interventions.
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