Detecting drug-drug interactions using a database for spontaneous adverse drug reactions: an example with diuretics and non-steroidal anti-inflammatory drugs.
OBJECTIVE
Drug-drug interactions are relatively rarely reported to spontaneous reporting systems (SRSs) for adverse drug reactions. For this reason, the traditional approach for analysing SRS has major limitations for the detection of drug-drug interactions. We developed a method that may enable signalling of these possible interactions, which are often not explicitly reported, utilising reports of adverse drug reactions in data sets of SRS. As an example, the influence of concomitant use of diuretics and non-steroidal anti-inflammatory drugs (NSAIDs) on symptoms indicating a decreased efficacy of diuretics was examined using reports received by the Netherlands Pharmacovigilance Foundation Lareb.


METHODS
Reports received between 1 January 1990 and 1 January 1999 of patients older than 50 years were included in the study. Cases were defined as reports with symptoms indicating a decreased efficacy of diuretics, non-cases as all other reports. Exposure categories were the use of NSAIDs or diuretics versus the use of neither of these drugs. The influence of the combined use of both drugs was examined using logistic regression analysis.


RESULTS
The odds ratio of the statistical interaction term of the combined use of both drugs was increased [adjusted odds ratio 2.0, 95% confidence interval (CI) 1.1-3.7], which may indicate an enhanced effect of concomitant drug use.


CONCLUSIONS
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.
van Puijenbroek
E P
EP
Netherlands Pharmacovigilance Foundation Lareb, Hertogenbosch. e.vanpuijenbroek@lareb.nl
Egberts
A C
AC
Heerdink
E R
ER
Leufkens
H G
HG
D016907:Adverse Drug Reaction Reporting Systems / Q000706:statistics & numerical data*; D000367:Age Factors; D000368:Aged; D000894:Anti-Inflammatory Agents, Non-Steroidal / Q000009:adverse effects*; D016208:Databases, Factual; D004232:Diuretics / Q000009:adverse effects*; D004347:Drug Interactions; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D014944:World Health Organization
D000894:Anti-Inflammatory Agents, Non-Steroidal; D004232:Diuretics