Identification of novel signal of DRESS associated with antibiotics: a disproportionality analysis of the FDA adverse event reporting system (FAERS) database

Abstract

Purpose: Antibiotics are widely used in the management of bacterial infections However; most antibiotics are not known for DRESS. Our objective is to find out the association of DRESS with available antibiotics using disproportionality analysis.

Methods: Retrospective pharmacovigilance disproportionality analysis based on the FDA Adverse Event Reporting System (FAERS) database from a period of 2004 Q1- 2022 Q3 was conducted using OpenVigil 2.1 tool. Disproportionality measures like Proportional reporting Ratio with associated Chi- square values (PRR ≥ 2 with associated χ2 ≥ 4), ROR with a 95% confidence interval (lower limit of 95% C.I. of ROR is greater than 1), and the number of cases of co-occurrence (n) were used for the identification of novel signals.

Results: A total of 13,918 cases of DRESS were reported, out of which 5,455 cases were found with various classes of antibiotics. The signal of DRESS was identified with a total of 40 antibiotics. Sub groups analysis results have shown variation in the strength of signal based on gender, age groups and geographical locations. The sensitivity analysis results have shown a decrease in the strength of signal after removal of cases of concomitant drugs.

Conclusion: 22 antibiotics were identified which can be associated with DRESS; however, further causality assessment is required to confirm the association.

Keywords: ADR; Antibiotics; DRESS syndrome; Drug-induced hypersensitivity syndrome; FAERS; Signal.