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 Adverse event profiles of dipeptidyl peptidase-4 inhibitors: data mining of the public version of the FDA adverse event reporting system

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Jing Huang ◽  
Yuntao Jia ◽  
Shusen Sun ◽  
Long Meng
Keyword(s):  
Data Mining ◽  
Adverse Event ◽  
Adverse Events ◽  
Reporting System ◽  
Adverse Event Reporting System ◽  
Dipeptidyl Peptidase ◽  
Adverse Event Reporting ◽  
Event Reporting ◽  
Dipeptidyl Peptidase 4 ◽  
Dipeptidyl Peptidase 4 Inhibitors

Abstract Background To describe and analyze the patterns of adverse events associated with dipeptidyl peptidase-4 inhibitors (DPP-4is) (sitagliptin, saxagliptin, linagliptin, vildagliptin, and alogliptin) from the FDA Adverse Event Reporting System (FAERS) and to highlight areas of safety concerns. Methods Adverse events spontaneously submitted to the FAERS between 2004 Q1 to 2019 Q2 were included. The online tool OpenVigil 2.1 was used to query the database. The research relied on definitions of preferred terms (PTs) specified by the Medical Dictionary for Regulatory Activities (MedDRA) and the standardized MedDRA Queries (SMQ). The reporting odds ratio (ROR), with 95% confidence intervals (CIs) was calculated for disproportionality analysis. Results Over 16 years, a total of 9706 adverse event reports were identified. Alogliptin was excluded from further analysis due to insufficient sample size. Compared with the non-insulin antidiabetic drugs, the four DPP-4is were all disproportionately associated with four SMQs: “gastrointestinal nonspecific inflammation and dysfunctional conditions,” “hypersensitivity,” “severe cutaneous adverse reactions,” and “noninfectious diarrhoea”. As for PT level analyses, DPP-4is are associated with higher reporting of the gastrointestinal tract, pancreas, malignancies, infection, musculoskeletal disorders, general disorders, hypersensitivity, and skin AEs. Conclusions Data mining of the FAERS is useful for examining DPP-4 inhibitors-associated adverse events. The findings of the present study are compatible with clinical experience, and it provides valuable information to decision-makers and healthcare providers in clinical practice.

scholarly journals Systematic analysis of safety profile for darunavir and its boosted agents using data mining in the FDA Adverse Event Reporting System database

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiaojiang Tian ◽  
Yao Yao ◽  
Guanglin He ◽  
Yuntao Jia ◽  
Kejing Wang ◽  
...  
Keyword(s):  
Data Mining ◽  
Adverse Event ◽  
Reporting System ◽  
Proportional Reporting Ratio ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Reporting Odds Ratio ◽  
Systematic Analysis ◽  
Event Reporting ◽  
Exfoliative Dermatitis

AbstractThis current investigation was aimed to generate signals for adverse events (AEs) of darunavir-containing agents by data mining using the US Food and Drug Administration Adverse Event Reporting System (FAERS). All AE reports for darunavir, darunavir/ritonavir, or darunavir/cobicistat between July 2006 and December 2019 were identified. The reporting Odds Ratio (ROR), proportional reporting ratio (PRR), and Bayesian confidence propagation neural network (BCPNN) were used to detect the risk signals. A suspicious signal was generated only if the results of the three algorithms were all positive. A total of 10,756 reports were identified commonly observed in hepatobiliary, endocrine, cardiovascular, musculoskeletal, gastrointestinal, metabolic, and nutrition system. 40 suspicious signals were generated, and therein 20 signals were not included in the label. Severe high signals (i.e. progressive extraocular muscle paralysis, acute pancreatitis, exfoliative dermatitis, acquired lipodystrophy and mitochondrial toxicity) were identified. In pregnant women, umbilical cord abnormality, fetal growth restriction, low birth weight, stillbirth, premature rupture of membranes, premature birth and spontaneous abortion showed positive signals. Darunavir and its boosted agents induced AEs in various organs/tissues, and were shown to be possibly associated with multiple adverse pregnant conditions. This study highlighted some novel and severe AEs of darunavir which need to be monitored prospectively.

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