Lack of essential information in spontaneous reports of adverse drug reactions in Catalonia—a restraint to the potentiality for signal detection

Lorraine Plessis, Ainhoa Gómez, Núria García, Gloria Cereza, Albert Figueras

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    12 Citations (Scopus)

    Abstract

    © 2017, Springer-Verlag Berlin Heidelberg. Purpose: The aim of this study is to analyze the quality of the information contained in the adverse drug reactions (ADR) reports and to describe the magnitude and characteristics of the lacking information. Methods: All reports of serious ADR received by the Catalan Center of Pharmacovigilance in 2014 were analyzed using the VigiGrade and a more clinical and qualitative approach. Results: Up to 824 reports describing serious ADR were included in the study; of them, 503 (61.0%) were sent by health care professionals (HPs) and the remaining 321 (39.0%) came from pharmaceutical companies (PhC). More than 80% of missing variables such as ‘onset date’ or ‘time-to-onset’ of the ADR were from PhCs reports. ‘Onset of treatment date’ was not filled in 28 (22.2%) of the reports including an ‘additional monitoring’ medicine, and ‘end of treatment’ date was not completed in 53 of those reports (42.1%). In summary, 39% of the reports involving a black triangle medicine sent by PhCs lacked some essential information such as the onset date of treatment. Conclusions: More than one third of the reports coming from manufacturers did not include information that is considered a limiting factor to evaluate any causal relationship, and can be an issue for the detection of safety signals. To take advantage of this huge amount of potentially important information that is almost useless at present, data mining tools and new algorithms should be developed and tested with the aim of finding formulas to deal with a huge amount of low quality data without losing it, nor generating a number of false associations.
    Original languageEnglish
    Pages (from-to)751-758
    JournalEuropean Journal of Clinical Pharmacology
    Volume73
    DOIs
    Publication statusPublished - 1 Jun 2017

    Keywords

    • Data mining
    • Database
    • Pharmaceutical industry
    • Pharmacovigilance

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