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Background: The Stevens-Johnson syndrome (SJS) is a severe skin reaction to non-steroidal anti-inflammatory drugs (NSAIDs), and can even be life-threatening. However, there are still few real-world studies to compare the specific differences in the adverse effects of skin and mucosal invasion. Methods: Disproportionality analysis and Bayesian analysis were devoted to data-mining of the suspected SJS after using NSAIDs based on the FDA's Adverse Event Reporting System (FAERS) from January 2004 to March 2021. The times to onset, fatality, and hospitalization rates of antipyretic analgesic-associated SJS were also investigated. Results: A total of 1,868 reports of SJS adverse events were identified with NSAIDs. Among 5 NSAIDs monotherapies we studied (acetaminophen, ibuprofen, aspirin, diclofenac and celecoxib), ibuprofen had the highest association with SJS based on the highest reporting odds ratio (ROR = 7.06, 95% two-sided CI = 6.59-7.56), proportional reporting ratio (PRR = 6.98, χ2 = 4201.14) and empirical Bayes geometric mean (EBGM = 6.78, 95% one-sided CI = 6.40). However, ibuprofen-associated SJS had the lowest fatality rate (6.87%, p < 0.0001) and the highest hospitalization rate (79.27%, p < 0.0001). Celecoxib-associated SJS had the latest time to onset (317.56 days, p < 0.0001). Diclofenac-associated SJS cases appeared to be associated with the highest risk of death (25.00%, p < 0.0001). Conclusions: The analysis of FAERS data provides a more accurate profile of the incidence and prognosis of SJS after NSAIDs treatment, enabling continued surveillance and timely intervention in patients at risk of SJS following these NSAIDs.
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Aims: We aimed to estimate the risk of drug-induced liver injury (DILI) from various antifungal treatments with azoles and echinocandins causing in real-world practice. Methods: We performed disproportionality and Bayesian analyses based on data from the first quarter in 2004 to the third quarter in 2021 in the Food and Drug Administration Adverse Event Reporting System to characterize the signal differences of antifungal drugs-related DILI. We also compared the onset time and mortality differences of different antifungal agents. Results: A total of 2943 antifungal drugs-related DILI were identified. Affected patients tended to be aged >45 years (51.38%), with more males than females (49.03% vs. 38.09%). Antifungal drug-induced liver injury is most commonly reported with voriconazole (32.45%), fluconazole (19.37%), and itraconazole (14.51%). Almost all antifungal drugs were shown to be associated with DILI under disproportionality and Bayesian analyses. The intraclass analysis of correlation between different antifungal agents and DILI showed the following ranking: caspofungin (ROR = 6.12; 95%CI: 5.36-6.98) > anidulafungin (5.15; 3.69-7.18) > itraconazole (5.06; 4.58-5.60) > voriconazole (4.58; 4.29-4.90) > micafungin (4.53; 3.89-5.27) > posaconazole (3.99; 3.47-4.59) > fluconazole (3.19; 2.93-3.47) > ketoconazole (2.28; 1.96-2.64). The onset time of DILI was significantly different among different antifungal drugs (p < 0.0001), and anidulafungin result in the highest mortality rate (50.00%), while ketoconazole has the lowest mortality rate (9.60%). Conclusion: Based on the Food and Drug Administration Adverse Event Reporting System database, antifungal drugs are significantly associated with DILI, and itraconazole and voriconazole had the greatest risk of liver injury. Due to indication bias, more clinical studies are needed to confirm the safety of echinocandins.
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Background: Although kidney injury has been reported as a serious adverse effect in patients treated with ibuprofen or acetaminophen (APAP), there are still few real-world studies to compare the specific differences in the adverse effects of nephrotoxicity. Methods: Disproportionality analysis and Bayesian analysis were devoted to data-mining of the suspected kidney injury after using ibuprofen and APAP based on the FDA's Adverse Event Reporting System (FAERS) from January 2004 to March 2021. The times to onset, fatality, and hospitalization rates of ibuprofen-associated kidney injury and APAP-associated kidney injury were also investigated. Results: 2,453 reports of ibuprofen-associated kidney injury and 1,288 reports of APAP-associated kidney injury were identified. Ibuprofen appeared to affected more middle-aged patients than elderly ones (27.76 vs 16.53%) while APAP appeared to affected more young patients than middle-aged patients (45.24 vs 29.10%) and elderly patients were fewer (13.99%). Compared to ibuprofen, APAP had the higher association with renal injury based on the higher reporting odds ratio (ROR = 2.45, 95% two-sided CI = 2.36-2.56), proportional reporting ratio (PRR = 2.39, χ 2 = 2002.94) and empirical Bayes geometric mean (EBGM = 2.38, 95% one-sided CI = 2.3). In addition, APAP-associated kidney injury had earlier onset (32.74 vs 115.82 days, p < 0.0001) and a higher fatality rate (44.43 vs 7.36%, p < 0.001) than those of ibuprofen-associated kidney injury. Conclusion: The analysis of FAERS data provides a more accurate profile on the incidence and prognosis of kidney injury after ibuprofen and acetaminophen treatment, enabling continued surveillance and timely intervention in patients at risk of kidney injury using these drugs.
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BACKGROUND: Ginkgolide B (GKB) is a major active component of the extracts of Ginkgo biloba leaves, and it has been used as an anti-cancer agent. However, it is unknown whether GKB has the therapeutic effects on lung cancer. Here, we studied the effects of GKB on lung cancer cells. METHODS: The effects of GKB on lung cancer cell proliferation and invasion were analyzed by cell counting kit (CCK-8) and cell invasion assays, respectively. Apoptosis was detected by flow cytometry. Western blot analysis was used to confirm the expression of autophagy-associated proteins in GKB-treated cells. Immunofluorescence analysis was used to analyze the level of light chain 3B (LC3B). RESULTS: Treatment with GKB time-dependently inhibited the proliferation and decreased the invasive capacity of A549 and H1975 cells. GKB induced apoptosis of these cells, but there was no significant effect on apoptosis compared to the control treatment. GKB-induced inhibition of cell proliferation and GKB-induced cell death were due to autophagy rather than apoptosis. GKB-induced autophagy of lung cancer cells was dependent on beclin-1, and autophagy-induced inhibition of the NLRP3 inflammasome contributed to the anti-tumor effect of GKB. CONCLUSIONS: GKB-mediated autophagy of lung cancer cells is beclin-1-dependent and results in inhibition of the NLRP3 inflammasome. Therefore, GKB might be a potential therapeutic candidate for the treatment of lung cancer.