Article
Signal generation in the database of the German Net of Regional Pharmacovigilance Centers
Methoden der Signalgenerierung in der Datenbank des Netzwerks Regionaler Pharmakovigilanzzentren
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Authors
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Marietta Rottenkolber
- Institute for Medical Informatics, Biometry and Epidemiology, Ludwigs-Maximilians-Universität München, Munich, Germany
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Joerg Hasford
- Institute for Medical Informatics, Biometry and Epidemiology, Ludwigs-Maximilians-Universität München, Munich, Germany
| Published: | November 6, 2008 |
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Outline
Text
Background and aim: It has been repeatedly shown that Spontaneous Reporting Systems are the most effective monitoring source about adverse drug reactions (ADRs) after drug approval. One disadvantage of such a system is the unknown number of exposed persons. So it is impossible to estimate reliable incidence rates. For that reason signal detection measures are developed.
Material and method: ADRs causing hospitalization to departments of internal medicine are collected in the database of the German Net of Regional Pharmacovigilance Centers since 1996. This database is mined with the common measures of disproportionality, the Proportional Reporting Ratio [1], the Reporting Odds Ratio [2], and the Empirical Bayes Geometric Mean [3]. Additionally, the data are analyzed with a lasso regression model.
Results: The database of the German Net of Regional Pharmacovigilance Centers contains approximately 8,000 reports. The commonly used measures all analyse a fourfold contingency table, separately for each drug-ADR combination. The aim of these methods is to find combinations which show a great difference between observed and expected number of reports. Because these methods only focus on ‘single drugs – single event’ combinations, they completely ignore confounding, especial confounding by concomitant medication. Many combinations are just highlighted because the drug is given always with another drug that elicits the ADR. To reduce the number of false positive signals, we use a logistic regression technique to analyse the data. With lasso regression models [4] we can correct the results for confounding and analyse the influence of many drugs simultaneously.
Conclusion: The measures of disproportionality analyse only ‘single drug - single event’ combinations. Because ADRs are often induced by interactions of two or more drugs other methods like the lasso regression model are more appropriate to find such combinations.
Data Collection was supported by BfArM: Fo. V-5329/68605/2008-2010
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