Detecting drug–drug interactions using a database for spontaneous adverse drug reactions: an example with diuretics and non-steroidal anti-inflammatory drugs

Puijenbroek, van Eugène; Egberts, Toine C. G.; Heerdink, Eibert R.; Leufkens, H.G.M.

doi:10.1007/s002280000215

Cited by 112 publications

(91 citation statements)

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“…Measures of disproportionality have also been proposed in order to detect drug interactions [15][16][17]. Recently a disproportionality measure (Omega) was developed to study the co-reporting of two drugs and one ADR in order to detect drug interactions [18] in the World Health Organization (WHO)-ADR database, called VigiBase [19].…”

Section: Introductionmentioning

confidence: 99%

Rhabdomyolysis a result of azithromycin and statins: an unrecognized interaction

Strandell

Bate

Hägg

et al. 2009

Brit J Clinical Pharma

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WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Rhabdomyolysis is a serious but rare adverse effect of statins. • The mechanism of rhabdomyolysis with statins is poorly defined, but the occurrence is known to increase with dose/ concentration. • Some macrolides are known to interact with statins; however, azithromycin has not been described to interact with statins with the exception of two literature case reports. WHAT THIS STUDY ADDS • A case series in the World Health Organization Adverse Drug Reaction (WHO‐ADR) database was suggestive of a possible drug interaction between statins and azithromycin with rhabdomyolysis. • A disproportionality measure, Omega, was shown to identify previously not recognized suspected drug interactions within the WHO‐ADR dataset. 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.

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Section: Introductionmentioning

confidence: 99%

Rhabdomyolysis a result of azithromycin and statins: an unrecognized interaction

Strandell

Bate

Hägg

et al. 2009

Brit J Clinical Pharma

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“…23,24) Logistic regression offers the advantageous possibility of controlling for covariates and it can be used to analyze the use of interaction terms in more detail. [23][24][25] However, other research groups have criticized the use of logistic regression to assess drug interactions. 35) Although research on the performance, accuracy, and reliability of different data mining algorithms is in progress, there is no recognized gold standard methodology.…”

Section: Discussionmentioning

confidence: 99%

“…22) It may be acceptable to compare several RORs of a particular event derived from stratified analysis within a particular context to examine the possibility of an interaction between two drugs and a single event (drug-drug interaction). 23,24) The effects of drug combinations can be studied using a statistical interaction term in a logistic model to calculate the RORs. [22][23][24][25] To our knowledge, our study was the first to evaluate the effects of the interactions between PPIs, clopidogrel, and aspirin using the FAERS database.…”

Section: Analysis Of the Interaction Betweenmentioning

confidence: 99%

Analysis of the Interaction between Clopidogrel, Aspirin, and Proton Pump Inhibitors Using the FDA Adverse Event Reporting System Database

Suzuki

Umetsu

et al. 2015

Biological & Pharmaceutical Bulletin

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“…15,16) The pharmacovigilance index, termed the reporting odds ratio (ROR), was developed to detect drug-associated adverse events in the spontaneous reporting database, and is not applicable for evaluating the comparative strength of causalities. 17) However, the ROR is applicable to a logistic regression model, which allows for the control of covariates. 15,17) We evaluated the possible relationship between oseltamivir use and NPAEs from data available in the FAERS databases using the ROR and logistic regression analysis.…”

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confidence: 99%

“…17) However, the ROR is applicable to a logistic regression model, which allows for the control of covariates. 15,17) We evaluated the possible relationship between oseltamivir use and NPAEs from data available in the FAERS databases using the ROR and logistic regression analysis.…”

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confidence: 99%

Analysis of Neuropsychiatric Adverse Events in Patients Treated with Oseltamivir in Spontaneous Adverse Event Reports

Ueda

Umetsu

Abe

et al. 2015

Biological & Pharmaceutical Bulletin

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There have been concerns that oseltamivir causes neuropsychiatric adverse events (NPAEs). We analyzed the association of age and gender with NPAEs in patients treated with oseltamivir using a logistic regression model. NPAE data were obtained from the U.S. Food and Drug Administration Adverse Event Reporting System (2004 to 2013). The lower limit of the reporting odds ratio (ROR) 95% confidence interval (CI) of "abnormal behavior" in Japan, Singapore, and Taiwan was ≥1. The effects of the interaction terms for oseltamivir in male patients aged 10-19 years were statistically significant. The adjusted ROR of "abnormal behavior" was 96.4 (95% CI, 77.5-119.9) in male patients aged 10-19 years treated with osletamivir. In female patients, the results of the likelihood ratio test for "abnormal behavior" were not statistically significant. The adjusted NPAE RORs were increased in male and female patients under the age of 20 years. Oseltamivir use could be associated with "abnormal behavior" in males aged 10-19 years. After considering the causality restraints of the current analysis, further epidemiological studies are recommended.

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Detecting drug–drug interactions using a database for spontaneous adverse drug reactions: an example with diuretics and non-steroidal anti-inflammatory drugs

Abstract: The findings illustrate that spontaneous reporting systems have a potential for signal detection and the analysis of possible drug-drug interactions. The method described may enable a more active approach in the detection of drug-drug interactions after marketing.

Cited by 112 publications

References 0 publications

Rhabdomyolysis a result of azithromycin and statins: an unrecognized interaction

Rhabdomyolysis a result of azithromycin and statins: an unrecognized interaction

Analysis of the Interaction between Clopidogrel, Aspirin, and Proton Pump Inhibitors Using the FDA Adverse Event Reporting System Database

Analysis of Neuropsychiatric Adverse Events in Patients Treated with Oseltamivir in Spontaneous Adverse Event Reports

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