Suspected Adverse Drug Reaction Detection using Association Rules Mining and Fuzzy sets

2022 ◽  
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pp. 36-45
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Ayman Mansour
2018 ◽  
Vol 17 (4) ◽  
pp. 339-345 ◽  
Author(s):  
Daniel Caldeira ◽  
Raquel Rodrigues ◽  
Daisy Abreu ◽  
Ana Marta Anes ◽  
Mário M. Rosa ◽  
...  

2016 ◽  
Vol 44 (12) ◽  
pp. 304-304
Author(s):  
Jaclyn LeBlanc ◽  
Pamela Smithburger ◽  
Shawn Kram ◽  
Sandra Kane-Gill

PLoS ONE ◽  
2012 ◽  
Vol 7 (10) ◽  
pp. e46022 ◽  
Author(s):  
Janine Arnott ◽  
Hannah Hesselgreaves ◽  
Anthony J. Nunn ◽  
Matthew Peak ◽  
Munir Pirmohamed ◽  
...  

2015 ◽  
Vol 100 (Suppl 3) ◽  
pp. A10.3-A11
Author(s):  
J Arnott ◽  
AJ Nunn ◽  
H Mannix ◽  
M Peak ◽  
M Pirmohamed ◽  
...  

Drug Safety ◽  
2012 ◽  
Vol 35 (10) ◽  
pp. 837-844 ◽  
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Betsabé Sánchez-Sánchez ◽  
Marina Altagracia-Martínez ◽  
Jaime Kravzov-Jinich ◽  
Consuelo Moreno-Bonett ◽  
Everardo Vázquez-Moreno ◽  
...  

2020 ◽  
Author(s):  
Daniele Sartori ◽  
Jeffrey Aronson ◽  
Igho Onakpoya

Abstract Background: Signals of adverse drug reactions are the basis of some regulatory risk-minimization actions in pharmacovigilance, such as changes to the section of undesirable effects in Summaries of Products Characteristics (SmPCs). Reviews of the evidence of signals have highlighted that these are mostly supported by reports of adverse drug reactions or multiple types of evidence, but have so far been limited to specific medicinal products, time intervals, groups of adverse drug reactions and specific countries. The time that elapses between a report of a suspected adverse drug reaction and the communication of a signal has not been systematically investigated. Furthermore, difficulties in causally linking medicinal products to adverse events have been highlighted, but the elements of reports of suspected ADRs that authors used to support putative causal relationships have been rarely characterized.Methods: We plan a scoping review to chart the evidence underpinning signals in pharmacovigilance and the time that it takes to communicate a signal. We shall retrieve records from electronic databases, without language or publication restrictions; we shall apply backward and forward citation to adjust for variations in database indexing. We shall also hand-search the websites of 35 regulatory agencies/authorities, restricted publications from Uppsala Monitoring Centre, and drug bulletins in the list of International Society of Drug Bulletins. If websites do not report signals, signals will be requested from the competent stakeholder. We shall use the Oxford Centre for Evidence-Based Medicine Levels of Evidence to chart and summarize evidence. We shall use VigiBase, the World Health Organization’s Global Individual Case Safety Report database, to determine the date of reporting for reports of adverse drug reactions. Plots, or pictograms (if appropriate), will be used to represent the time from the first report of a suspected adverse drug reaction to a signal.Discussion: We expect that the findings from this exploratory investigation will be useful in better understanding global patterns of similarities or differences in regulatory decision-making in terms of evidence and timing of communications, and in identifying relevant research questions for future systematic reviews.Scoping review registration: osf.io/jtv38


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