Association of antiviral drugs and their possible mechanisms with DRESS syndrome using data mining algorithms
Antiviral 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 antiviral drugs and their possible mechanism with DRESS. Data mining algorithms such as proportional reporting ratio that is, PRR (≥2) wi...
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| Published in: | Journal of medical virology Vol. 95; no. 3; pp. e28671 - n/a |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
United States
Wiley Subscription Services, Inc
01.03.2023
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| Subjects: | |
| ISSN: | 0146-6615, 1096-9071, 1096-9071 |
| Online Access: | Get full text |
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| Summary: | Antiviral 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 antiviral drugs and their possible mechanism with DRESS. Data mining algorithms such as proportional reporting ratio that is, PRR (≥2) with associated χ2 value (>4), reporting odds ratio that is, 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 antiviral drugs with possible targets. The potential signal of DRESS was found to be associated with abacavir, acyclovir, ganciclovir, lamivudine, lopinavir, nevirapine, ribavirin, ritonavir, and zidovudine among all selected antiviral 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 human leukocyte antigen (HLA)*B1502 and HLA*B5801. The positive signal of DRESS was found with selected antiviral drugs except for acyclovir. |
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| Bibliography: | Akash Sharma and Sweta Roy contributed equally to this work. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ISSN: | 0146-6615 1096-9071 1096-9071 |
| DOI: | 10.1002/jmv.28671 |