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 spontan eous reporting systems (SRSs) for adverse drug reactions. For this reason, the traditional approach for analysing SRS has major limitations for the de tection of drug-drug interactions. We developed a method that may enable si gnalling of these possible interactions, which are often not explicitly rep orted, 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 effica cy of diuretics was examined using reports received by the Netherlands Phar macovigilance Foundation Lareb. Methods: Reports received between 1 January 1990 and 1 January 1999 of pati ents older than 50 years were included in the study. Cases were defined as reports with symptoms indicating a decreased efficacy of diuretics, non-cas es as all other reports. Exposure categories were the use of NSAIDs or diur etics versus the use of neither of these drugs. The influence of the combin ed use of both drugs was examined using logistic regression analysis. Resul ts: The odds ratio of the statistical interaction term of the combined use of both drugs was increased [adjusted odds ratio 2.0, 95% confidence interv al (CI) 1.1-3.7], which may indicate an enhanced effect of concomitant drug use. Conclusion: The findings illustrate that spontaneous reporting systems have a potential for signal detection and the analysis of possible drug-drug in teractions. The method described may enable a more active approach in the d etection of drug-drug interactions after marketing.