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• W2920796312 abstract "We analyzed the spontaneous adverse event database in Singapore to determine the types of cutaneous adverse drug reactions (CADRs) and causative drugs reported. We selected 10 CADRs-of-interest, and identified the suspected drugs and the characteristics of the at-risk population. ADR reports received from 2006 to 2015 of the system organ class “Skin and Appendages Disorders” were analyzed based on patient demographics, the types of CADRs, suspected drugs, outcome, and latency period. Of the 104 372 reports analyzed, 56.2% involved females and 72.5% involved Chinese patients. The mean age was 41.1 years old. The top CADRs reported were rash (including nonspecified rash, follicular rash, maculopapular rash, and vesicular rash) (67.2%) and angioedema (13.9%). The drugs frequently associated with the CADRs-of-interest include nonsteroidal antiinflammatory drugs and antibiotics with angioedema, iohexol with urticaria, and antiepileptics and allopurinol with Stevens-Johnson syndrome (SJS)/toxic epidermal necrolysis (TEN). A subgroup analysis based on age, sex, and race on the 10 CADRs-of-interest showed the following trends in reporting: Alopecia (reported more in females), drug hypersensitivity syndrome (more in males), angioedema (more in younger patients), and photosensitivity (more in older patients). In general, the racial distribution across each CADR-of-interest was consistent with that of Singapore's population, with slight deviations observed for SJS/TEN, photosensitivity and skin discoloration. We analyzed CADR reports from Singapore over 10 years, and identified the types of CADRs reported, and their associated drugs, latency periods and patient characteristics. Such information could add value to healthcare professionals as they assess CADR cases and evaluate suspected drugs." @default.
• W2920796312 created "2019-03-22" @default.
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• W2920796312 date "2019-03-13" @default.
• W2920796312 modified "2023-10-16" @default.
• W2920796312 title "Spontaneous cutaneous adverse drug reaction reports—An analysis of a 10‐year dataset in Singapore" @default.
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• W2920796312 doi "https://doi.org/10.1002/prp2.469" @default.
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