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• W2022144328 abstract "Better evidence regarding drug safety in the pediatric population might be generated from existing data sources such as spontaneous reporting systems and electronic healthcare records. The Global Research in Paediatrics (GRiP)–Network of Excellence aims to develop pediatric-specific methods that can be applied to these data sources. A reference set of positive and negative drug–event associations is required. The aim of this study was to develop a pediatric-specific reference set of positive and negative drug–event associations. Considering user patterns and expert opinion, 16 drugs that are used in individuals aged 0–18 years were selected and evaluated against 16 events, regarded as important safety outcomes. A cross-table of unique drug–event pairs was created. Each pair was classified as potential positive or negative control based on information from the drug’s Summary of Product Characteristics and Micromedex. If both information sources consistently listed the event as an adverse event, the combination was reviewed as potential positive control. If both did not, the combination was evaluated as potential negative control. Further evaluation was based on published literature. Selected drugs include ibuprofen, flucloxacillin, domperidone, methylphenidate, montelukast, quinine, and cyproterone/ethinylestradiol. Selected events include bullous eruption, aplastic anemia, ventricular arrhythmia, sudden death, acute kidney injury, psychosis, and seizure. Altogether, 256 unique combinations were reviewed, yielding 37 positive (17 with evidence from the pediatric population and 20 with evidence from adults only) and 90 negative control pairs, with the remainder being unclassifiable. We propose a drug–event reference set that can be used to compare different signal detection methods in the pediatric population." @default.
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• W2022144328 date "2015-02-01" @default.
• W2022144328 modified "2023-10-18" @default.
• W2022144328 title "Pediatric Drug Safety Signal Detection: A New Drug–Event Reference Set for Performance Testing of Data-Mining Methods and Systems" @default.
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• W2022144328 doi "https://doi.org/10.1007/s40264-015-0265-0" @default.
• W2022144328 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4328124" @default.
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