Combining big data search analytics and the FDA Adverse Event Reporting System database to detect a potential safety signal of mirtazapine abuse

Dimitrios Spachos, Spyridon Siafis, Panagiotis Bamidis, Dimitrios Kouvelas, Georgios Papazisis

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

This study sought to detect a potential safety signal of mirtazapine abuse by combining two different sources of surveillance, specifically Google Analytics (Google, Inc., Mountain View, CA, USA) and the FDA Adverse Event Reporting System database. Data from the first quarter of 2004 to the second quarter of 2017 were collected and analysed. The search interest over time, the frequencies of abuse-related terms in the search analytics domain, and the odds ratio of abuse events in FDA Adverse Event Reporting System were determined. Correlations between the two aforementioned domains using quarterly data from the timeline series were also assessed. Our results suggest a positive correlation between abuse-related searches in the Google domain and abuse-related events in FDA Adverse Event Reporting System database. These results indicate that these methods can be used in combination with each other as a pharmacovigilance supplementary tool to detect drug safety signals.

Original languageEnglish
Pages (from-to)2265-2279
Number of pages15
JournalHealth Informatics Journal
Volume26
Issue number3
DOIs
StatePublished - 1 Sep 2020
Externally publishedYes

Keywords

  • big data
  • FAERS database
  • Google search analytics
  • mirtazapine abuse
  • safety signal

Fingerprint

Dive into the research topics of 'Combining big data search analytics and the FDA Adverse Event Reporting System database to detect a potential safety signal of mirtazapine abuse'. Together they form a unique fingerprint.

Cite this