Purpose <p>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.</p> Methods <p>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.</p> Results <p>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.</p> Conclusion <p>22 antibiotics were identified which can be associated with DRESS; however, further causality assessment is required to confirm the association.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

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

  • Khushi Goyal,
  • Ruchika Sharma,
  • Ashok Kumar Datusalia,
  • Gopal L. Khatik,
  • Anoop Kumar

摘要

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.