Dagyeom Jung, Inkyung Jung.
Abstract
Several statistical methods have been proposed to detect adverse drug reactions induced by taking two drugs together. These suspected adverse drug reactions can be discovered through post-market drug safety surveillance, which mainly relies on spontaneous reporting system database. Most previous studies have applied statistical models to real world data, but it is not clear which method outperforms the others. We aimed to assess the performance of various detection methods by implementing simulations under various conditions.
Introduction
Polypharmacy, the use of multiple medicines has increased as the average life expectancy and the prevalence of multimorbidity has increased. Adverse events (AEs) caused by the administration of many drugs at the same time are therefore a serious concern. These suspected adverse drug reactions (ADRs) due to drug-drug interaction (DDI) can be discovered through post-market drug safety surveillance (PMS). Spontaneous reporting systems (SRSs) are databases used for PMS that include ADR reports and prescription information (e.g, sex, age, date, quantity, etc).
Materials and Methods:
We conducted a simulation study to evaluate the performances of the methods reviewed in the previous section. We considered four different sets of scenarios. Although the basic idea for setting the parameters was adopted from the study by Gosho et al. We created more various situations. While they only considered the additive assumption for an interaction effect, we considered both the additive (scenario sets 1 and 2) and multiplicative (scenario sets 3 and 4) assumptions.
Discussion
As the number of patients with chronic disease becomes more common, the co-prescription of multiple drugs has increased. Therefore, it has become more important to identify combinations of drugs that have side effects through post-market drug safety surveillance. In this article, we examined statistical methodologies for DDI signal detection. Of the six methods, the Ω shrinkage method and the chi-square method showed the best performance.
Citation: Jung D, Jung I (2024) A simulation-based comparison of drug-drug interaction signal detection methods. PLoS ONE 19(4): e0300268. https://doi.org/10.1371/journal.pone.0300268
Editor: Jed N. Lampe, University of Colorado Denver Skaggs School of Pharmacy and Pharmaceutical Sciences, UNITED STATES
Received: April 4, 2023; Accepted: February 25, 2024; Published: April 17, 2024.
Copyright: © 2024 Jung, Jung. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The dataset used in the present study cannot be publicly shared. Qualified researchers can request access to the KAERS database through the Korea Institute of Drug Safety and Risk Management by visiting https://open.drugsafe.or.kr/original/invitation.jsp.
Funding: IJ received National Research Foundation of Korea grant by the Korean government (MSIT) (No. 2021R1F1A1060156). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
