Abstract

BackgroundSignals of adverse drug reactions (ADRs) form the basis of some regulatory risk-minimization actions in pharmacovigilance. Reviews of limited scope have highlighted that such signals are mostly supported by reports of ADRs or multiple types of evidence. The time that elapses between a report of a suspected ADR and the communication of a signal has not been systematically characterized. Neither has the features of reports of suspected ADRs that authors used to support putative causal relationships, although difficulties with establishing causal relationships between medicinal products and adverse events have been highlighted. The objectives of this study will be to describe the evidence underpinning signals in pharmacovigilance, the features of reports of ADRs supporting signals, and the time that it takes to communicate a signal.MethodsWe shall retrieve records from PubMed, EMBASE, Web of Science, and PsycINFO (from inception onwards), without language/design restrictions, and apply backward citation screening. We shall hand-search the websites of 35 regulatory agencies/authorities, restricted publications from the Uppsala Monitoring Centre, and drug bulletins. Signals will be requested from the competent stakeholder, if absent from websites. We shall use VigiBase, the World Health Organization’s Global Individual Case Safety Report database, to determine the dates on which ADRs were reported. We shall manage records using EndNote (v. 8.2); one reviewer will screen titles/abstracts and full texts, a second will cross-validate the findings, and a third will arbitrate disagreements. Data will be charted via the Systematic Reviews Data Repository, following the same procedures as for data retrieval. Evidence will be categorized according to the Oxford Centre for Evidence-Based Medicine Levels of Evidence. Features of reports of ADRs will be coded. Tables will display frequencies of types of evidence and features of reports of ADRs. We shall use plots or pictograms (if appropriate) to represent the time from the first report of a suspected ADR to a signal.DiscussionWe expect the findings from this review will allow a better understanding of global patterns of similarities or differences in terms of supporting evidence and timing of communications and identify relevant research questions for future systematic reviews.Systematic review registrationosf.io/a4xns

Highlights

  • Signals of adverse drug reactions (ADRs) form the basis of some regulatory risk-minimization actions in pharmacovigilance

  • Comparative assessments of signals discussed at the Pharmacovigilance Risk Assessment Committee have suggested that reports of ADRs often supported signals, but that support from multiple sources of evidence increased the likelihood of regulatory action [8, 9]

  • The review protocol has been registered in the Open Science Framework database and is being reported in accordance with the reporting guidance provided in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) statement [33, 34]

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Summary

Introduction

Signals of adverse drug reactions (ADRs) form the basis of some regulatory risk-minimization actions in pharmacovigilance. A systematic review of definitions, later adopted by the Council for International Organizations of Medical Sciences, defined a signal in pharmacovigilance as “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 verificatory and, when necessary, remedial actions” [1, 2] Based on this definition, a signal can be supported by diverse levels of evidence, ranging from one or more reports of suspected adverse drug reactions (ADRs) to observational studies and randomized clinical trials [3,4,5]. Regulatory actions, appear to be inconsistent across international settings; discrepancies in communications of the same risks of drug-induced harms in healthcare systems have been recorded, and it has been suggested that they may be better understood by characterizing the strength of the underpinning evidence [12, 13]

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