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Reporting Patterns Indicative of Adverse Drug Interactions: A Systematic Evaluation in VigiBase
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. Uppsala Monitoring Centre, Sweden.
Stockholm University, Faculty of Science, Department of Mathematics. Uppsala Monitoring Centre, Sweden.
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2011 (English)In: Drug Safety, ISSN 0114-5916, E-ISSN 1179-1942, Vol. 34, no 3, 253-266 p.Article in journal (Refereed) Published
Abstract [en]

Background: Adverse drug interaction surveillance in collections of Individual Case Safety Reports (ICSRs) remains underdeveloped. Most efforts to date have focused on disproportionality analysis, but the empirical support for its value is based on isolated examples. Additionally, too little attention has been given to the potential value of the detailed content of ICSRs for improved adverse drug interaction surveillance.

Objective: The aim of the study was to identify reporting patterns indicative of suspected adverse drug interactions before the drug interactions are generally established.

Methods: A reference set of known adverse drug interactions and drug pairs not known to interact was constructed from information added to Stockley's Drug Interactions Alerts between the first quarter of 2007 and the third quarter of 2009. The reference set was used to systematically study differences in reporting patterns between adverse drug interactions before they are generally established and adverse drug reactions (ADRs) to drug pairs that are not known to interact, in the WHO Global ICSR Database, VigiBase. The scope of the study included pharmacological properties such as common cytochrome P450 metabolism, explicit suspicions of drug interactions as noted by the reporter, clinical details such as dose and treatment overlap, and the lower limit of the 95% credibility interval of a three-way measure of disproportionality, Omega025025), based on the total number of reports on two drugs and one ADR together. Analyses were carried out including and excluding concomitant medicines.

Results: Five reporting patterns were highlighted as particularly strong indicators of adverse drug interactions before they are known: suspicion of interactions as noted by the reporter in a case narrative, the assignment of the two drugs as interacting or through an ADR term; co-reporting of effect increased with the drug pair; and, finally, an excess total number of reports on the ADR together with the two drugs, as measured by Ω025. Overall, the inclusion of concomitant medicines led to a larger number of true adverse drug interactions being highlighted, but at a substantial decrease in the strength of most indicators. Notably, the inclusion of concomitant medicines completely eliminated the value of Ω025 as an indicator of adverse drug interactions, in this systematic evaluation.

Conclusions: Reported suspicion of interactions as noted by the reporter in a case narrative, the assignment of the two drugs as interacting or through an ADR term; co-reporting of effect increased with the drug pair and by the Ω025 each provide unique information to highlight adverse drug interactions before they become known in the literature. To our knowledge, this is the first systematic analysis demonstrating the value of disproportionality analysis for adverse drug interactions using a comprehensive reference set, and the first study to consider a broader basis including clinical information for systematic drug interaction surveillance.

Place, publisher, year, edition, pages
2011. Vol. 34, no 3, 253-266 p.
National Category
Information Science
Research subject
Computer and Systems Sciences; hälso- och sjukvårdsforskning; Mathematical Statistics
Identifiers
URN: urn:nbn:se:su:diva-55288DOI: 10.2165/11586990-000000000-00000ISI: 000288349500008OAI: oai:DiVA.org:su-55288DiVA: diva2:402273
Available from: 2011-03-07 Created: 2011-03-07 Last updated: 2017-12-11Bibliographically approved

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