liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Reporting Patterns Indicative of Adverse Drug Interactions: A Systematic Evaluation in VigiBase.
Linköping University, Department of Medical and Health Sciences, Clinical Pharmacology. Linköping University, Faculty of Health Sciences.
Uppsala Monitoring Centre, Uppsala Sweden. Department of Computer and Systems Sciences, Stockholm University, Stockholm, Sweden.
Uppsala Monitoring Centre, Uppsala Sweden. School if Information Systems, Brunel University, London, UK.
Uppsala Monitoring Centre, Uppsala Sweden. Department of Mathematics, Stockholm University, Stockholm, Sweden.
Show others and affiliations
2011 (English)In: Drug Safety, ISSN 0114-5916, E-ISSN 1179-1942, Vol. 34, no 3, 253-66 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, Omega(025) (Ω(025)), 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 Ω(025). 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 Ω(025) 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 Ω(025) 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
Adis International , 2011. Vol. 34, no 3, 253-66 p.
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:liu:diva-66510DOI: 10.2165/11586990-000000000-00000ISI: 000288349500008PubMedID: 21332249OAI: oai:DiVA.org:liu-66510DiVA: diva2:404780
Available from: 2011-03-18 Created: 2011-03-18 Last updated: 2017-12-11Bibliographically approved
In thesis
1. Drug interaction surveillance using individual case safety reports
Open this publication in new window or tab >>Drug interaction surveillance using individual case safety reports
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Background: Drug interactions resulting in adverse drug reactions (ADRs) represent a major health problem both for individuals and society in general. Post-marketing pharmacovigilance reporting databases with compiled individual case safety reports (ICSRs) have been shown to be particularly useful in the detection of novel drug - ADR combinations, though these reports have not been fully used to detect adverse drug interactions.

Aim: To explore the potential to identify drug interactions using ICSRs and to develop a method to facilitate the detection of adverse drug interaction signals in the WHO Global ICSR Database, VigiBase.

Methods: All six studies included in this thesis are based on ICSRs available in VigiBase. Two studies aimed to characterise drug interactions reported in VigiBase. In the first study we examined if contraindicated drug combinations (given in a reference source of drug interactions) were reported on the individual reports in the database, and in the second study we examined the scientific literature for interaction mechanisms for drug combinations most frequently co-reported as interacting in VigiBase. Two studies were case series analyses where the individual reports were manually reviewed. The two remaining studies aimed to develop a method to facilitate detection of novel adverse drug interactions in VigiBase. One examined what information (referred to as indicators) was reported on ICSRs in VigiBase before the interactions became listed in the literature. In the second methodological study, logistic regression was used to set the relative weights of the indicators to form triage algorithms. Three algorithms (one completely data driven, one semi-automated and one based on clinical knowledge) based on pharmacological and reported clinical information and the relative reporting rate of an ADR with a drug combination were developed. The algorithms were then evaluated against a set of 100 randomly selected case series with potential adverse drug interactions. The algorithm’s performances were then evaluated among DDAs with high coefficients.

Results: Drug interactions classified as contraindicated are reported on the individual reports in VigiBase, although they are not necessarily recognised as interactions when reported. The majority (113/123) of drug combinations suspected for being responsible for an ADR were established drug interactions in the literature. Of the 113 drug interactions 46 (41%) were identified as purely pharmacodynamic; 28 (25%) as pharmacokinetic; 18 (16%) were a mix of both types and for 21 (19%) the mechanism have not yet been identified. Suspicions of a drug interaction explicitly noted by the reporter are much more common for known adverse drug interactions than for drugs not known to interact. The clinical evaluation of the triage algorithms showed that 20 were already known in the literature, 30 were classified as signals and 50 as not signals. The performance of the semi-automated and the clinical algorithm were comparable. In the end the clinical algorithm was chosen. At a relevant level, 38% were of the adverse drug interactions were already known in the literature and of the remaining 80% were classified as signals for this algorithm.

Conclusions: This thesis demonstrated that drug interactions can be identified in large post-marketing pharmacovigilance reporting databases. As both pharmacokinetic and pharmacodynamic interactions were reported on ICSRs the surveillance system should aim to detect both. The proposed triage algorithm had a high performance in comparison to the disproportionality measure alone.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2011. 45 p.
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1252
Keyword
Adverse drug reactions, adverse drug interaction surveillance, drug interactions, individual case safety reports, postmarketing pharmacovigilance, signal detection
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-70424 (URN)978-91-7393-106-9 (ISBN)
Public defence
2011-10-06, Nils Holger, Campus US, Linköpings universitet, Linköping, 13:00 (English)
Opponent
Supervisors
Available from: 2011-09-07 Created: 2011-09-07 Last updated: 2011-09-20Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textPubMed

Authority records BETA

Strandell, Johanna

Search in DiVA

By author/editor
Strandell, Johanna
By organisation
Clinical PharmacologyFaculty of Health Sciences
In the same journal
Drug Safety
Medical and Health Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 61 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf