Review of Statistical Methodologies for Detecting Drug–Drug Interactions Using Spontaneous Reporting Systems - Noguchi, Yoshihiro; Tachi, Tomoya; Teramachi, Hitomi (Frontiers in Pharmacology, 2019)
Polypharmacy situations, which is the use of multiple concomitant drugs to treat a medical condition, is recognized as social problem. The concomitant use of 2 or more drugs increases the risk of AEs. This problem is generally known as drug-drug interactions (DDIs), the proportion of AEs due to DDIs is estimated to be up to 30% of unexpected AEs. In pre-marketing randomized clinical trials, patients on multiple drug use are usually excluded because the focus is on establishing the safety and efficacy of a single drug and not on investigating drug-drug interactions (DDIs). However, unlike pre-marketing randomized clinical trials, in clinical practice (= post marketing), many patients use multiple drugs, as in polypharmacy situations. The spontaneous reporting systems are a crucial source of post-marketing drug safety surveillance and are commonly used to detect suspected drug-induced adverse events (AEs) and generate hypothesized unknown drug-induced AEs in real-world settings. Recently, not only methodological studies on signal detection of “single” drug, but also on several methodological studies on signal detection of DDIs have been conducted. On the other hand, there are few articles that systematically summarize the statistical methodology for signal detection of DDIs. Therefore, this article reviews the studies on the latest statistical methodologies from classical methodologies for signal detection of DDIs using spontaneous reporting system. This article describes how to calculate for each detection method and the major findings from the published literatures about DDIs. Finally, this article presented some of the challenges related to the currently used methodologies for signal detection of DDIs and suggestions for further studies.