Abstract
The reporting odds ratio (ROR) is easy to calculate, and there have been several examples of its use because of its potential to speed up the detection of drug–drug interaction signals by using the “upward variation of ROR score”. However, since the validity of the detection method is unknown, this study followed previous studies to investigate the detection trend. The statistics models (the Ω shrinkage measure and the “upward variation of ROR score”) were compared using the verification dataset created from the Japanese Adverse Drug Event Report database (JADER). The drugs registered as “suspect drugs” in the verification dataset were considered as the drugs to be investigated, and the target adverse event in this study was Stevens–Johnson syndrome (SJS), as in previous studies. Of 3924 pairs that reported SJS, the number of positive signals detected by the Ω shrinkage measure and the “upward variation of ROR score” (Model 1, the Susuta Model, and Model 2) was 712, 2112, 1758, and 637, respectively. Furthermore, 1239 positive signals were detected when the Haldane–Anscombe 1/2 correction was applied to Model 2, the statistical model that showed the most conservative detection trend. This result indicated the instability of the positive signal detected in Model 2. The ROR scores based on the frequency-based statistics are easily inflated; thus, the use of the “upward variation of ROR scores” to search for drug–drug interaction signals increases the likelihood of false-positive signal detection. Consequently, the active use of the “upward variation of ROR scores” is not recommended, despite the existence of the Ω shrinkage measure, which shows a conservative detection trend.
Highlights
To ensure the proper use of drugs, it is important to understand the related adverse events
Of the 374,327 cases used in this study, there were 3924 drug D1 –drug D2 -Stevens–Johnson syndrome (SJS), wherein the number of positive signals was 712 for the Ω shrinkage measure [16]; 2,112 for Model 1; 1758 for the Susuta model; and 637 for Model 2
Model 2, 1239 positive signals were detected when Haldane–Anscombe 1/2 correction was applied to Model 2, which, was the statistical model that showed the most conservative detection trend
Summary
To ensure the proper use of drugs, it is important to understand the related adverse events. Pre-marketing randomized clinical trials focus on establishing the safety and efficacy of a single drug, rather than investigating drug–drug interactions. Unlike pre-marketing studies, in actual clinical practice, multiple drugs are generally used for treatment. Recent reports have estimated that the proportion of adverse events caused by drug–. Drug interactions is approximately 30% of unexpected adverse events [1]. Considering the numerous reports on polypharmacy in treatment in recent years [2,3,4,5,6], early identification of adverse events that may be caused by drug–drug interactions is an important issue that should be addressed
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