Drug-Related Hypertension: A Disproportionality Analysis Leveraging the FDA Adverse Event Reporting System

Abstract

Hypertension exerts a significant global disease burden, adversely affecting the well-being of billions. Alarmingly, drug-related hypertension remains an area that has not been comprehensively investigated. Therefore, this study is designed to utilize the adverse event reports (AERs) from the US Food and Drug Administration's Adverse Event Reporting System (FAERS) to more comprehensively identify drugs that may potentially lead to hypertension. Specifically, a total of 207 233 AERs were extracted from FAERS, spanning the time period from 2004 to 2024. Based on these reports, this study presented the top 40 drugs most frequently reported to be associated with post-administration hypertension in different genders. Furthermore, we employed four disproportionality analysis methods, including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Empirical Bayes Geometric Mean (EBGM), to pinpoint the top three drugs with strongest signals in relation to hypertension across different age and gender subgroups. Some drugs, such as rofecoxib, lenvatinib, and celecoxib, were found to appear on both the frequency and signal strength lists. These results contribute to a more comprehensive understanding of the cardiovascular safety profiles of pharmacological agents, suggesting the necessity of blood pressure monitoring following administration.