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Strandell, Johanna
Publications (10 of 10) Show all publications
Strandell, J., Noren, N. G. & Hägg, S. (2013). Key Elements in Adverse Drug Interaction Safety Signals An Assessment of Individual Case Safety Reports. Drug Safety, 36(1), 63-70
Open this publication in new window or tab >>Key Elements in Adverse Drug Interaction Safety Signals An Assessment of Individual Case Safety Reports
2013 (English)In: Drug Safety, ISSN 0114-5916, E-ISSN 1179-1942, Vol. 36, no 1, p. 63-70Article in journal (Refereed) Published
Abstract [en]

Background A large proportion of potential drug interactions are known from pre-authorization studies, but adverse drug reactions (ADRs) due to interactions (adverse drug interactions) are often first detected through astute observation in clinical practice. Individual case safety reports (ICSRs) are collected from broad patient populations and allow for the identification of groups of similar reports. Systematic screening for adverse drug interactions in ICSRs will require an understanding of which information on these reports can be suggestive of adverse drug interactions. less thanbrgreater than less thanbrgreater thanObjective The aim of the study was to identify what reported information may support the identification of drug interaction safety signals in collections of ICSRs. less thanbrgreater than less thanbrgreater thanMethods Three previously published safety signals of suspected adverse drug interactions were re-evaluated. To this end, 137 reports related to these signals were retrieved from the WHO Global ICSR Database, VigiBase (TM), and corresponding original reports were obtained from national pharmacovigilance centres. Criteria from an operational score for causality analysis of drug interactions of clinical cases, the Drug Interaction Probability Scale (DIPS), were applied to each of these reports with the aim of identifying what supportive information tends to be available in ICSRs. For three DIPS elements (plausible time course, resolution of the ADR after terminating the drug inducing the interaction without changes in affected drug therapy (positive dechallenge) and alternative causes of the reaction) we also compared the amount of information in VigiBase (TM) and in original reports, and in free text and structured data. less thanbrgreater than less thanbrgreater thanResults Commonly fulfilled DIPS elements on reports supporting an adverse drug interaction signal were plausible time course (50 reports; 36 %) and positive dechallenge (8 reports; 6 %). Alternative causes for the observed adverse reaction were observed in 72 (53 %) reports. We found limited differences between VigiBase (TM) and original reports for the structured data, although a substantial amount of additional information was available in free text in original reports. less thanbrgreater than less thanbrgreater thanConclusions Information on plausible time courses and resolution of the adverse reaction upon withdrawal of the drug suspected to have induced the interaction may be a useful element in identifying suspected adverse drug interactions from ICSRs. Of these, plausible time course is by far the most commonly reported element in the three signals studied here. Our analysis also demonstrated the importance of sharing and analysing information available in free text where relevant clinical details are often available, such as those mentioned above, along with severity and dosage changes.

Place, publisher, year, edition, pages
Adis, 2013
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-91347 (URN)10.1007/s40264-012-0003-9 (DOI)000316357700007 ()
Available from: 2013-04-22 Created: 2013-04-22 Last updated: 2017-12-06
Strandell, J., Caster, O., Hopstadius, J., Edwards, R. I. & Noren, N. G. (2013). The Development and Evaluation of Triage Algorithms for Early Discovery of Adverse Drug Interactions. Drug Safety, 36(5), 371-388
Open this publication in new window or tab >>The Development and Evaluation of Triage Algorithms for Early Discovery of Adverse Drug Interactions
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2013 (English)In: Drug Safety, ISSN 0114-5916, E-ISSN 1179-1942, Vol. 36, no 5, p. 371-388Article in journal (Refereed) Published
Abstract [en]

Background Around 20 % of all adverse drug reactions (ADRs) are due to drug interactions. Some of these will only be detected in the postmarketing setting. Effective screening in large collections of individual case safety reports (ICSRs) requires automated triages to identify signals of adverse drug interactions. Research so far has focused on statistical measures, but clinical information and pharmacological characteristics are essential in the clinical assessment and may be of great value in first-pass filtering of potential adverse drug interaction signals. less thanbrgreater than less thanbrgreater thanObjective The aim of this study was to develop triages for adverse drug interaction surveillance, and to evaluate these prospectively relative to clinical assessment. less thanbrgreater than less thanbrgreater thanMethods A broad set of variables were considered for inclusion in the triages, including cytochrome P450 (CYP) activity, explicit suspicions of drug interactions as noted by the reporter, dose and treatment overlap, and a measure of interaction disproportionality. Their unique contributions in predicting signals of adverse drug interactions were determined through logistic regression. This was based on the reporting in the WHO global ICSR database, VigiBase (TM), for a set of known adverse drug interactions and corresponding negative controls. Three triages were developed, each producing an estimated probability that a given drug-drug-ADR triplet constitutes an adverse drug interaction signal. The triages were evaluated against two separate benchmarks derived from expert clinical assessment: adverse drug interactions known in the literature and prospective adverse drug interaction signals. For reference, the triages were compared with disproportionality analysis alone using the same benchmarks. less thanbrgreater than less thanbrgreater thanResults The following were identified as valuable predictors of adverse drug interaction signals: plausible CYP metabolism; notes of suspected interaction by the reporter; and reports of unexpected therapeutic response, altered therapeutic effect with dose information and altered therapeutic effect when only two drugs had been used. The new triages identified reporting patterns corresponding to both prospective signals of adverse drug interactions and already established ones. They perform better than disproportionality analysis alone relative to both benchmarks. less thanbrgreater than less thanbrgreater thanConclusions A range of predictors for adverse drug interaction signals have been identified. They substantially improve signal detection capacity compared with disproportionality analysis alone. The value of incorporating clinical and pharmacological information in first-pass screening is clear.

Place, publisher, year, edition, pages
Adis, 2013
National Category
Social Sciences
Identifiers
urn:nbn:se:liu:diva-94322 (URN)10.1007/s40264-013-0053-7 (DOI)000318788500008 ()
Available from: 2013-06-24 Created: 2013-06-24 Last updated: 2017-12-06
Aagaard, L., Strandell, J., Melskens, L., Petersen, P. S. G. & Holme Hansen, E. (2012). Global Patterns of Adverse Drug Reactions Over a Decade Analyses of Spontaneous Reports to VigiBase (TM). Drug Safety, 35(12), 1171-1182
Open this publication in new window or tab >>Global Patterns of Adverse Drug Reactions Over a Decade Analyses of Spontaneous Reports to VigiBase (TM)
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2012 (English)In: Drug Safety, ISSN 0114-5916, E-ISSN 1179-1942, Vol. 35, no 12, p. 1171-1182Article in journal (Refereed) Published
Abstract [en]

Background: Although systems to collect information about suspected adverse drug reactions (ADRs) were established in many countries and by the WHO in the 1960s, few studies have examined reported ADRs related to national income. Objective: The aim of the study was to characterize ADRs reported to the WHO-ADR database, VigiBase (TM), and to relate data to national income. Methods: We analysed ADR reports submitted to VigiBase (TM) from 2000 to 2009 with respect to reporting rate, age and sex of patient, type, seriousness and medications. Reports were also analysed with respect to national income level, classified in accordance with the World Bank definition: low, lower-middle, upper-middle and high. Results: We analysed 1 359 067 ADR reports including 3 013 074 ADRs. Overall, 16% of reports were serious and 60% were reported for females. High-income countries had the highest ADR reporting rates (range 3-613 reports/million inhabitants/year) and low-income countries the lowest (range 0-21). Distribution of ADRs across income groups with respect to age group, seriousness and sex was non-significant. Overall, the majority of ADRs were reported for nervous system medications, followed by cardiovascular medicines. Low-income countries reported relatively more ADRs for antiinfectives for systemic use than high-income countries, and high-income countries reported more ADRs for antineoplastic and immunomodulating agents than lower-income groups. Conclusion: This study showed that high-income countries had the highest ADR reporting rates and low-income countries the lowest, with large variations across countries in each group. Significant differences in ADR reporting rates were only found for ADRs of the type skin and subcutaneous tissue disorders and for the therapeutic groups antiinfectives for systemic use and antineoplastic and immunomodulation agents. To strengthen ADR reporting rates, especially in low-income countries, more research is needed about the impact of organizational structures and economic resources of national pharmacovigilance centres and ADR reporting practices on the large variations in ADR reporting rates within income groups.

Place, publisher, year, edition, pages
Adis, 2012
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-87986 (URN)10.2165/11631940-000000000-00000 (DOI)000311533100009 ()
Available from: 2013-01-28 Created: 2013-01-28 Last updated: 2017-12-06
Strandell, J. (2011). Drug interaction surveillance using individual case safety reports. (Doctoral dissertation). Linköping: Linköping University Electronic Press
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. p. 45
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1252
Keywords
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
Strandell, J. & Wahlin, S. (2011). Pharmacodynamic and pharmacokinetic drug interactions reported to VigiBase, the WHO global individual case safety report database.. European Journal of Clinical Pharmacology, 67(6), 633-641
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, p. 633-641Article 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
Keywords
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
Strandell, J., Caster, O., Bate, A., Norén, N. & Edwards, I. R. (2011). Reporting Patterns Indicative of Adverse Drug Interactions: A Systematic Evaluation in VigiBase.. Drug Safety, 34(3), 253-66
Open this publication in new window or tab >>Reporting Patterns Indicative of Adverse Drug Interactions: A Systematic Evaluation in VigiBase.
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2011 (English)In: Drug Safety, ISSN 0114-5916, E-ISSN 1179-1942, Vol. 34, no 3, p. 253-66Article 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
Strandell, J., Bate, A., Hägg, S. & Edwards, I. R. (2009). Rhabdomyolysis a result of azithromycin and statins: an unrecognized interaction. British Journal of Clinical Pharmacology, 68(3), 427-34
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, p. 427-34Article 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
Keywords
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
Strandell, J., Bate, A., Lindquist, M. & Edwards, I. R. (2008). Letter: Drug-drug interactions - a preventable patient safety issue? [Letter to the editor]. British Journal of Clinical Pharmacology, 65(1), 144-146
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, p. 144-146Article in journal, Letter (Other academic) Published
Abstract [en]

n/a

Place, publisher, year, edition, pages
Wiley, 2008
Keywords
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
Strandell, J., Norén, N. G. & Hägg, S.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.

Keywords
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
Strandell, J., Caster, O., Hopstadius, J., Edwards, R. & Norén, N.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
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(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.

Keywords
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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