Postmarketing hepatic adverse event experience with PEGylated/non-PEGylated drugs: a disproportionality analysis

2007 ◽  
Vol 19 (11) ◽  
pp. 934-941 ◽  
Author(s):  
Manfred Hauben ◽  
Ferdinando Vegni ◽  
Lester Reich ◽  
Muhammad Younus
Keyword(s):  
Adverse Event ◽  
Disproportionality Analysis ◽  
Hepatic Adverse Event

Novel Adverse Events of Iloperidone: A Disproportionality Analysis in US Food and Drug Administration Adverse Event Reporting System (FAERS) Database

2019 ◽  
Vol 14 (1) ◽  
pp. 21-26 ◽  
Author(s):  
Viswam Subeesh ◽  
Eswaran Maheswari ◽  
Hemendra Singh ◽  
Thomas Elsa Beulah ◽  
Ann Mary Swaroop
Keyword(s):  
Data Mining ◽  
Adverse Event ◽  
Adverse Events ◽  
Reporting System ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Disproportionality Analysis ◽  
Positive Signal ◽  
Data Mining Algorithms ◽  
Mining Algorithms

Background: The signal is defined as “reported information on a possible causal relationship between an adverse event and a drug, of which the relationship is unknown or incompletely documented previously”. Objective: To detect novel adverse events of iloperidone by disproportionality analysis in FDA database of Adverse Event Reporting System (FAERS) using Data Mining Algorithms (DMAs). Methodology: The US FAERS database consists of 1028 iloperidone associated Drug Event Combinations (DECs) which were reported from 2010 Q1 to 2016 Q3. We consider DECs for disproportionality analysis only if a minimum of ten reports are present in database for the given adverse event and which were not detected earlier (in clinical trials). Two data mining algorithms, namely, Reporting Odds Ratio (ROR) and Information Component (IC) were applied retrospectively in the aforementioned time period. A value of ROR-1.96SE>1 and IC- 2SD>0 were considered as the threshold for positive signal. Results: The mean age of the patients of iloperidone associated events was found to be 44years [95% CI: 36-51], nevertheless age was not mentioned in twenty-one reports. The data mining algorithms exhibited positive signal for akathisia (ROR-1.96SE=43.15, IC-2SD=2.99), dyskinesia (21.24, 3.06), peripheral oedema (6.67,1.08), priapism (425.7,9.09) and sexual dysfunction (26.6-1.5) upon analysis as those were well above the pre-set threshold. Conclusion: Iloperidone associated five potential signals were generated by data mining in the FDA AERS database. The result requires an integration of further clinical surveillance for the quantification and validation of possible risks for the adverse events reported of iloperidone.

scholarly journals Drug-Induced Liver Injury Associated with Lopinavir- Ritonavir in Patients with COVID-19: A Disproportionality Analysis of U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) Data

2021 ◽  
Author(s):  
Huilin Tang ◽  
Liyuan Zhou ◽  
Xiaotong Li ◽  
Alan C Kinlaw ◽  
Jeff Y Yang ◽  
...  
Keyword(s):  
Adverse Event ◽  
Liver Injury ◽  
Drug Administration ◽  
Reporting System ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Disproportionality Analysis ◽  
Drug Induced ◽  
Event Reporting ◽  
Drug Induced Liver Injury

Abstract Background Liver injury has been documented independently in novel coronavirus disease 2019 (COVID-19) patients and patients treated with lopinavir-ritonavir. Objective to investigate the drug-induced liver injury associated with lopinavir-ritonavir among the patients with COVID-19. Methods We conducted a disproportionality analysis of US Food and Drug Administration Adverse Event Reporting System (FAERS) between 2020Q1 and 2020Q3 to evaluate the association between lopinavir-ritonavir and risk of drug-induced liver injury (or severe drug-induced liver injury) and calculated their reporting odds ratios (RORs) with 95% confidence intervals (CIs). Results A total of 1,754 reports of drug-induced liver injury in patients with COVID-19. The ROR for drug-induced liver injury was 1.4 (95% CI, 1.1–1.7), 3.6 (95% CI, 2.7–4.7), and 0.8 (95% CI, 0.7-1.0) when comparing lopinavir-ritonavir with all other drugs, hydroxychloroquine/chloroquine only, and remdesivir, respectively. For severe drug-induced liver injury, RORs for lopinavir-ritonavir provided evidence of an association compared with all other drugs (ROR, 4.9; 95% CI, 3.7–6.5), compared with hydroxychloroquine/chloroquine only (ROR, 4.3; 95% CI, 3.0-6.2), and compared with remdesivir (ROR, 10.4; 95% CI, 7.2–15.0). Conclusions In the FAERS, we observed a disproportional signal for severe drug-induced liver injury associated with lopinavir-ritonavir in patients with COVID-19.

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