Association of antiviral drugs and their possible mechanisms with DRESS syndrome using data mining algorithms

Introduction Anti-viral drugs are not known for Drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome. The current study aims is to find out the association of anti-viral drugs and their possible mechanism with DRESS. Materials and Methods Data Mining Algorithms (DMAs) such as Proportional Reporting Ratio i.e., PRR (≥2) with associated Chi-square value (>4), Reporting Odds ratio i.e., ROR (≥2) with 95% confidence interval and case count (≥3) were calculated to identify a possible signal. Further, molecular docking studies were conducted to check the interaction of selected anti-viral drugs with possible targets. Results The potential signal of DRESS was found to be associated with abacavir, acyclovir, ganciclovir, lamivudine, lopinavir, nevirapine, ribavirin, ritonavir, and zidovudine among all selected anti-viral drugs. Further, subgroup analysis has also shown a potential signal in different age groups and gender. The sensitivity analysis results have shown a decrease in the strength of the signal, however, there was no significant impact on the outcome except for acyclovir. The docking results have indicated the possible involvement of HLA*B1502 and HLA*B5801. Conclusion The positive signal of DRESS was found with selected anti-viral drugs except for acyclovir. However, further causality assessment is required. This article is protected by copyright. All rights reserved.