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Drug interaction surveillance using individual case safety reports
Linköping University, Department of Medical and Health Sciences, Clinical Pharmacology. Linköping University, Faculty of Health Sciences.
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 [en]
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: urn:nbn:se:liu:diva-70424ISBN: 978-91-7393-106-9 (print)OAI: oai:DiVA.org:liu-70424DiVA: diva2:439241
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
List of papers
1. Letter: Drug-drug interactions - a preventable patient safety issue?
Open this publication in new window or tab >>Letter: Drug-drug interactions - a preventable patient safety issue?
2008 (English)In: British Journal of Clinical Pharmacology, ISSN 0306-5251, E-ISSN 1365-2125, Vol. 65, no 1, 144-146 p.Article in journal, Letter (Other academic) Published
Abstract [en]

n/a

Place, publisher, year, edition, pages
Wiley, 2008
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-70845 (URN)10.1111/j.1365-2125.2007.02981.x (DOI)17635497 (PubMedID)
Available from: 2011-09-20 Created: 2011-09-20 Last updated: 2017-12-08Bibliographically approved
2. Rhabdomyolysis a result of azithromycin and statins: an unrecognized interaction
Open this publication in new window or tab >>Rhabdomyolysis a result of azithromycin and statins: an unrecognized interaction
2009 (English)In: British Journal of Clinical Pharmacology, ISSN 0306-5251, E-ISSN 1365-2125, Vol. 68, no 3, 427-34 p.Article in journal (Refereed) Published
Abstract [en]

AIMS: In a systematic screening of the World Health Organization Adverse Drug Reaction database, VigiBase, in July 2008, a measure of association used to detect interactions (Omega) highlighted azithromycin with the individual statins atorvastatin, lovastatin and simvastatin and rhabdomyolysis. The aim was to examine all reports including rhabdomyolysis-azithromycin and statins in VigiBase to assess if the data were suggestive of an interaction.

METHODS: The individual case reports in VigiBase and the original files were reviewed. In order to investigate the reporting over time for rhabdomyolysis with azithromycin and statins to VigiBase, Omega values were generated retrospectively.

RESULTS: The reporting over time showed that rhabdomyolysis under concomitant use of azithromycin and statins was reported more often than expected from 2000 and onwards in Vigibase. After exclusion of possible duplicates and follow-up reports, 53 cases from five countries remained. Rhabdomyolysis occurred shortly after initiation of azithromycin in 23% of cases. In 11 patients an interaction had been suggested by the reporter. With the exception of one patient, the statin doses reported were within the recommended daily doses.

CONCLUSIONS: Case reports in VigiBase are suggestive that interactions between azithromycin and statins resulting in rhabdomyolysis may occur. This analysis showed the potential of the newly developed disproportionality measure, Omega, which can help to identify drug interactions in VigiBase in the future. The results also showed that reviewing spontaneous reports can add information to drug interactions not established previously.

Place, publisher, year, edition, pages
Wiley-Blackwell, 2009
Keyword
Adverse drug reaction reporting systems, azithromycin, disproportionality measure, drug interaction, statins, WHO-ADR database
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-70846 (URN)10.1111/j.1365-2125.2009.03473.x (DOI)000269575200015 ()19740401 (PubMedID)
Available from: 2011-09-20 Created: 2011-09-20 Last updated: 2017-12-08Bibliographically approved
3. Pharmacodynamic and pharmacokinetic drug interactions reported to VigiBase, the WHO global individual case safety report database.
Open this publication in new window or tab >>Pharmacodynamic and pharmacokinetic drug interactions reported to VigiBase, the WHO global individual case safety report database.
2011 (English)In: European Journal of Clinical Pharmacology, ISSN 0031-6970, E-ISSN 1432-1041, Vol. 67, no 6, 633-641 p.Article in journal (Refereed) Published
Abstract [en]

OBJECTIVE: Drug interactions resulting in adverse drug reactions (ADRs) represent a major health problem both for individuals and the community. Despite this, limited information is reported in the literature on the drug interaction categories responsible for causing ADRs. In the study reported here, we investigated the drug combinations most frequently co-reported as interacting in the WHO Global Individual Case Safety Report (ICSR) database, VigiBase, and categorised these according to the drug interaction mechanism. METHODS: Reports in which drug combinations were co-reported as interacting in at least 20 reports in VigiBase during the past 20 years were included in the study. Each drug combination was reviewed in the literature to identify the mechanism of interaction and subsequently classified as pharmacodynamic and/or pharmacokinetic reaction. Report characteristics were also analysed. RESULTS: A total of 3766 case reports of drug interactions from 47 countries were identified. Of the 123 different drug combinations reported, 113 were described in the literature to interact. The mechanism of the drug interaction was categorised as pharmacodynamic (46 combinations; 41%), pharmacokinetic (28; 25%), a combination of both types (18; 16%) and unidentified (21; 19%). Pharmacodynamic drug interactions primarily concerned pharmacological additive effects, whereas enzyme inhibition was the most frequent pharmacokinetic interaction. The combinations reviewed primarily implicated drugs such as warfarin, heparin, carbamazepine and digoxin. CONCLUSIONS: Drug interactions reported in globally collected ADR reports cover both pharmacodynamic, specifically additive pharmacological effects, and pharmacokinetic mechanisms primarily accredited to the inhibition of hepatic cytochrome P450 enzymes. These ADR reports often concern serious threats to patients' safety and are particularly related to the use of high risk drugs such as warfarin and heparin.

Place, publisher, year, edition, pages
Springer-Verlag New York, 2011
Keyword
Pharmacovigilance, VigiBase, Enzyme, inhibition, Additive effects
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-66507 (URN)10.1007/s00228-010-0979-y (DOI)000291607500010 ()21253716 (PubMedID)
Available from: 2011-03-18 Created: 2011-03-18 Last updated: 2017-12-11Bibliographically approved
4. Reporting Patterns Indicative of Adverse Drug Interactions: A Systematic Evaluation in VigiBase.
Open this publication in new window or tab >>Reporting Patterns Indicative of Adverse Drug Interactions: A Systematic Evaluation in VigiBase.
Show others...
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
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-66510 (URN)10.2165/11586990-000000000-00000 (DOI)000288349500008 ()21332249 (PubMedID)
Available from: 2011-03-18 Created: 2011-03-18 Last updated: 2017-12-11Bibliographically approved
5. Key Elements in Adverse Drug Interaction Safety Signals
Open this publication in new window or tab >>Key Elements in Adverse Drug Interaction Safety Signals
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Background: Effective surveillance of adverse drug interactions (a problematic drug combination resulting in an adverse drug reaction (ADR)) in large collections of individual case safety reports (ICSRs) requires a combination of expert clinical assessments and efficient algorithms. To date, most methods proposed for adverse drug interaction surveillance focus on disproportionality analysis, although a recent study proposed that the reported clinical and pharmacological information is also useful for systematic screening of adverse drug interactions.

Objective: The purpose of this study is to identify and describe key elements in adverse drug interaction safety signals.

Methods: Altogether 137 case reports from three previously published safety signals of suspected adverse drug interaction were re-evaluated using an operational algorithm for causality analysis of drug interactions; the Drug Interaction Probability Scale (DIPS). Reports in the WHO Global ICSR Database, VigiBase, and their corresponding original files were analysed, examining whether the DIPS elements were registered. The retrieved case information was specified as being listed in the structured fields, free text and, in total. In addition, information not covered by DIPS, such as explicit notifications of a suspected drug interaction by the reporter or the pharmacovigilance centre was also registered.

Results: As expected from the data used in this analysis, the most frequently fulfilled DIPS elements were: objective evidence (such as ADR) of a drug interaction (137 cases; 100%). Other frequent elements were (ranked order) plausible time to onset (53 cases; 38%), and resolution of the ADR after terminating the drug inducing the interaction (10 cases; 7%). Ten cases (7%) fulfilled both a plausible time to onset and resolution of the ADR after stopping the drug. Positive rechallenge was only reported in 3 cases (2%). For 32 cases additional information was reported in free text in the original files that were not available in VigiBase. A suspected drug interaction was noted by the reporter in 47 original cases (35%) and more than 80% of these were assessed as a possible or probable drug interaction according to the DIPS classification. Among cases without notes of suspected interactions were 58 original reports (64%) assessed as possible (56 cases) or probable (2 cases).

Conclusions: A plausible time to onset pattern and resolution of the ADR after withdrawal of the drug inducing the interaction frequently strengthened the suspected causality of a drug interaction. Particularly strong cases were those containing both these key elements. Since this information is often available in structured format, it could potentially be used to automatically highlight strong cases in firstpass screening. Finally, this analysis also demonstrated the importance of free text where particularly relevant clinically details such as timeliness, severity, resolution of the reaction after withdrawal of the drug inducing the interaction, possible alternative causes, and dosage changes are available.

Keyword
Adverse drug interactions, signals, systematic surveillance system, plausible time to onset
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-70847 (URN)
Available from: 2011-09-20 Created: 2011-09-20 Last updated: 2011-09-20Bibliographically approved
6. Triage algorithms for early discovery of adverse drug interactions
Open this publication in new window or tab >>Triage algorithms for early discovery of adverse drug interactions
Show others...
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Background: Most methodological research for broad surveillance of drug interactions in large collections of suspected ADR reports has focused on measures of disproportionality. However, recent results indicate that reported clinical information and pharmacological characteristics may be at least as valuable to detect adverse drug interactions early.

Objective: To develop triage algorithms for adverse drug interaction surveillance, and to evaluate the algorithms prospectively relative to expert clinical assessment.

Methods: A previously developed reference set based on Stockley’s Drug Interactions was used to train the algorithms. Logistic regression was used to set the relative weights of the different indicators (information potentially suggestive adverse drug interactions such as pharmacological properties including cytochrome P450 (CYP) activity; explicit suspicions of drug interactions as noted by the reporter in different forms; clinical details such as dose and treatment overlap; and a measure of disproportionality based on the total number of reports on two drugs and one ADR together) of each algorithm. Three triage algorithms were designed. All are logistic regression models producing an estimated probability that a given case series constitutes an adverse drug interaction signal. Two of them are data driven: one which used a very broad set of indicators (full data-driven) and one which used a more narrow set (lean data-driven). The third was manually derived (lean clinical) as a simplified version of the full data-driven algorithm. An independent evaluation set was constructed that consisted of 100 randomly selected case series in the WHO Global Individual Case Safety Report (ICSR) Database, VigiBase, from January 1990 to February 2011. Each algorithm’s ranking of case series was evaluated against an evaluation set. In a complementary analysis the algorithm were compared to a pure disproportionality analysis.

Results: The two lean algorithms were comparable in performance. However both outperformed the full data-driven algorithm on the independent evaluation set. The areas under the curve (AUC) for the receiver operating characteristics (ROC) curves were as follows: 71% (lean clinical) and 69% (lean data-driven). For a false positive rate (FPR) of up to 0.04 the lean algorithms classifies about 14,000 case series as potential interaction signals. Thresholds corresponding to greater FPRs are unlikely to be feasible in practice. The algorithms clearly outperform disproportionality analysis alone.

Conclusions: The value of incorporating clinical and pharmacological information in first-pass screening for adverse drug interactions is clear. Two triage algorithms have been proposed that each effectively identify adverse drug interaction signals and clearly outperforming pure disproportionality analysis in this respect.

Keyword
Individual Case Safety Reports, Adverse Drug Interactions, VigiBase, Triage algorithms
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-70848 (URN)
Available from: 2011-09-20 Created: 2011-09-20 Last updated: 2011-09-20Bibliographically approved

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