Multivariate generalized mixed-effects models for screening multiple adverse drug reactions in spontaneous reporting systems

• Published in: Frontiers in pharmacology 2024, Vol.15, p.1312803
• Main Authors: Gosho, Masahiko, Ishii, Ryota, Ohigashi, Tomohiro, Maruo, Kazushi
• Format: Article
• Language: English
• Subjects: drug-drug interaction; Pharmacology; proportional reporting rate; reporting odds ratio; signal detection
• ISSN: 1663-9812; 1663-9812
• DOI: 10.3389/fphar.2024.1312803

For assessing drug safety using spontaneous reporting system databases, quantitative measurements, such as proportional reporting rate (PRR) and reporting odds ratio (ROR), are widely employed to assess the relationship between a drug and a suspected adverse drug reaction (ADR). The databases contain numerous ADRs, and the quantitative measurements need to be calculated by performing the analysis multiple times for each ADR. We proposed a novel, simple, and easy-to-implement method to estimate the PRR and ROR of multiple ADRs in a single analysis using a generalized mixed-effects model for signal detection. The proposed method simultaneously analyzed the association between any drug and numerous ADRs, as well as estimated the PRR and ROR for a specific combination of drugs and suspected ADRs. Furthermore, the proposed method was applied to detect drug-drug interactions associated with the concurrent use of two or more drugs. In our simulation studies, the false-positive rate and sensitivity of the proposed method were similar to those of the traditional PRR and ROR. The proposed method detected known ADRs when applied to the Food and Drug Administration Adverse Event Reporting System database. As an important advantage, the proposed method allowed the simultaneous evaluation of several ADRs using multiple drugs.