A real-world disproportionality analysis of sacubitril/valsartan: data mining of the FDA adverse event reporting system.

ABSTRACT:

Purpose

Sacubitril/valsartan is extensively used in heart failure; however, there are few long-term safety studies of it in a wide range of populations. The aim of this study was to evaluate sacubitril/valsartan-induced adverse events (AEs) through data mining of the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS).

Methods

Reports in the FAERS from the third quarter of 2015 (FDA approval of sacubitril/valsartan) to the fourth quarter of 2023 were collected and analyzed. Disproportionality analyses, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian confidence propagation neural network (BCPNN), and empirical Bayesian geometric mean (EBGM) algorithms were adopted in data mining to quantify signals of sacubit

SUBMITTER: Wang Y 

PROVIDER: S-EPMC11347302 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature