Background: Nilotinib is a leukemia drug that can treat imatinib tolerance. During the drug trial, some adverse reactions of nilotinib have been proposed, and some articles have mentioned that nilotinib may have cardiovascular-related ADR signals. However, there is no systematic and comprehensive analysis of the potential ADR of nilotinib. AIM: The purpose of this study is to use the FDA adverse event reporting system (FAERS) database to detect the potential adverse event signals of nilotinib. Method: Data from the first quarter of 2015 to the fourth quarter of 2022 were selected for analysis from in the FAERS database. Use the preferred term in the Management activity Medical Dictionary (version 24.0) to extract cases of adverse events. The reported odds ratio (ROR) and information component (IC) methods based on statistical shrinkage transformation were used for disproportional analysis. Results: There were 24,451 adverse events associated with nilotinib in 11,190,626 records.A total of 529 positive signals of adverse reactions were found in taking nilotinib. Peripheral arterial occlusive disease (〖ROR〗_025=41.74 〖IC〗_025=5.36), Arteriosclerosis(〖ROR〗_025=33.49 〖IC〗_025=5.04), Intermittent claudication (〖ROR〗_025=32.12 〖IC〗_025=4.96), Splenitis (〖ROR〗_025=29.18 〖IC〗_025=4.79), Peripheral vascular disorder (〖ROR〗_025=27.00 〖IC〗_025=4.72), Peripheral artery stenosis (〖ROR〗_025=26.95 〖IC〗_025=4.96), Carotid artery stenosis (〖ROR〗_025=22.94 〖IC〗_025=4.48) had the strongest signal intensities. Conclusion: This study found that patients with leukemia taking nilotinib may have adverse reactions such as arteriovenous adverse reactions, myocardial infarction, splenitis, intermittent claudication and so on. KEYWORDS Disproportionate analysis, Nilotinib, FAERS database, pharmacovigilance study, CML

Background: Interleukin-23 (IL-23) inhibitors are widely used in clinical practice for Psoriasis , but multiple adverse events (AEs) have been reported. We aimed to describe the distribution of AEs related IL-23 inhibitors including Guselkumab, Tildrakizumab, Risankizumab, Ustekinumab. Methods: Data from January 1, 2014, to September 30, 2022 were extracted from the FDA Adverse Event Reporting System (FAERS). Disproportionality analysis including reporting odds ratio (ROR) and information component (IC) was performed to access potential signals. It was defined a signal when the lower limit of 95% confidence interval (CI) of ROR (ROR025) more than one or IC(IC025) exceeding zero, with the number of cases greater than or equal to three at the same time. Results: A total of 41,408,408 drug-AE reports were extracted from the FAERS database involving 13271168 people. 704, 13164, 62853, 11399 patients have used Tildrakizumab, Guselkumab, Ustekinumab, Risankizumab and 8, 20, 107 and 115 signals were found respectively. The “infections and infestations” has the highest incidence of SOC in Tildrakizumab(6/8), Guselkumab(5/20), Ustekinumab(50/107), Risankizumab(25/115). Conclusion: Our pharmacovigilance analysis showed that a high frequency was reported for AEs triggered by IL-23 inhibitors. IL-23 inhibitors had the potential to impair immune function resulting in a risk of infections or cancers. We need to pay special attention to Risankizumab because the drug has more AE occurrences than Ustekinumab despite Risankizumab has few reports than Ustekinumab and launched later than Ustekinumab.

Abstract Aim: We aim to compare nephrotoxic spectrum of IOCM and that of LOCM in a more intensive and comprehensive perspective using the real-world database. Methos: This is an observational, retrospective, pharmacovigilance study based on Vigibase. 7 products (iodixanol, iohexol, iopamidol, iopromide, iobitridol, ioversol and iomeprol) of ICM were included. Variable matching method was used for deduplication procedure. Two data mining method, reporting odds ratio (ROR) and bayesian confidence propagation neural networks of information components (IC) were used to detect signals for the full database, gender stratums (male and female), age stratum (0 to 64 years, 65 to 74 years and 75 or more years) and pooled analysis of total renal adverse events (AEs). Package ‘base’, ‘utils’ and ‘pheatmap’ of R language (version 4.1.2) were used to perform analysis and plot figures. Results: We got 2703 ICSRs and 3155 renal AE reports. The five most frequently reported were acute kidney injury, renal failure, renal impairment azotaemia and anuria. All ICM had highest signal value detected in age ≥75 years. Iodaxinal and iohexol had most signals detected. In pooled analysis of renal AEs, no signals detected for iopamidol, iomeprol and iopromide in the full database stratum. Conclusion: No evidence approved IOCM has safer nephrotoxicity than LOCM. CIN spectrum varies a lot within LOCM. Regarding to the whole population, not all products of ICM, such as iopamidol, iomeprol and iopromide, is likely to cause CIN.

Aim: Residual neuromuscular blockade is a common complication after general anaesthesia. Sugammadex can reverse the action of aminosteroid neuromuscular blockers. Our study aimed to explore sugammadex safety issues in the real world and determine the spectrum of adverse reactions. Methods: All sugammadex-related adverse events reported in VigiBase between 2010 and 2019 were classified by group queries according to the Medical Dictionary for Regulatory Activities. A disproportionality analysis of data was performed using the information component (IC); positive IC values were deemed significant. Results: Overall, 16,219,410 adverse events were reported, and 2032 were associated with sugammadex. The most frequent reactions were recurrence of neuromuscular blockade (n = 54, IC: 6.74, 95% credibility interval [CI]: 6.33–7.10), laryngospasm (n = 53, IC: 6.05, IC025:5.64), bronchospasm (n = 119, IC: 5.63 , IC025:5.36), and bradycardia (n = 169, IC: 5.13, IC025:4.90). Fatal cases were more likely with cardiac disorders, especially in patients over 65 years. In addition, the common adverse drug reactions (ADRs) differed between different age groups (P < 0.01). The ADRs were higher between 0–17 years than in other age groups. The onset time of common ADRs was typically within one day, and 68.9% occurred within half an hour after sugammadex administration. Conclusions: Anaesthesiologists should carefully monitor the anaesthesia recovery period to correct the adverse drug reactions caused by sugammadex and recommend monitoring neuromuscular function throughout the anaesthesia process. Sugammadex should be used carefully in patients with cardiovascular diseases, and ECG and hemodynamic changes monitored after medication.

Aim: With the widespread use of SGLT2i, various adverse events (AEs) have been reported. This study aimed to describe the distribution of SGLT2i-related AEs in different systems, quantify the association of important medical events (IMEs) and SGLT2i regimens, and build a signal profile of SGLT2i- induced IMEs. Methods: Data from 2015 Q1 to 2020 Q4 in the FDA Adverse Event Reporting System database (FAERS) were selected to conduct disproportionality analysis. Two signal indicators, the reported odds ratio (ROR) and information component (IC), were used to evaluate the correlation between SGLT2i and IMEs. The lower end of the 95% confidence interval of IC (IC025) exceeding zero was deemed a signal. For ROR, it was defined a signal if ROR025 over one, with at least 3 cases. Results: A total of 45,771,436 records were involved, including 111,564 records related to SGLT2i, with 38,366 records of SGLT2i-induced IMEs. Overall, SGLT2i was significantly associated with IMEs (IC=0.36, 95% CI: 0.35-0.38; ROR=1.44, 95% CI: 1.42-1.46). Most SGLT2i-related adverse events occurred in monotherapy (92.93%). Diabetic ketoacidosis was the most IMEs. Specifically, acute osteomyelitis has the strongest signal of all SGLT2i (IC025=7.83), and it was unique to canagliflozin. Diabetic ketoacidosis, acute kidney injury, ketoacidosis, Fournier’s gangrene, and euglycemic diabetic ketoacidosis were common to the four FDA-approved SGLT2i. Conclusion: Our study demonstrated that different SGLT2i regimens lead to different important adverse events, but there are overlapping events. Early identification and management of SGLT2i-associated IMEs are essential for clinical practice.