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.

scholarly journals Real-world Safety Profile of Darunavir and its Boosted Agents: An Analysis of FDA Adverse Event Reporting System Database

2021 ◽  
Author(s):  
Xiaojiang Tian ◽  
Yao Yao ◽  
Guanglin He ◽  
Yuntao Jia ◽  
Kejing Wang ◽  
...  
Keyword(s):  
Adverse Event ◽  
Adverse Drug Events ◽  
Reporting System ◽  
Proportional Reporting Ratio ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Reporting Odds Ratio ◽  
Event Reporting ◽  
Exfoliative Dermatitis ◽  
Adverse Pregnancy

Abstract This current investigation was aimed to generate signals for adverse drug events of darunavir-containing agents by data mining using the US Food and Drug Administration Adverse Event Reporting System (FAERS). All adverse event (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), 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 10756 AE reports were identified commonly observed in cardiovascular, endocrine, musculoskeletal, gastrointestinal, hepatobiliary, 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 associated with multiple adverse pregnancy conditions. This study highlighted some novel and severe AEs of darunavir which need to be monitored prospectively.

Adverse Drug Events in the Prevention and Treatment of COVID-19: A Data Mining Study on FDA Adverse Event Reporting System (FAERS) (Preprint)

2021 ◽  
Author(s):  
Qiang Guo ◽  
Shaojun Duan ◽  
Yaxi Liu ◽  
Yinxia Yuan
Keyword(s):  
Data Mining ◽  
Adverse Event ◽  
Adverse Drug Events ◽  
Reporting System ◽  
Proportional Reporting Ratio ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Drug Event ◽  
Event Reporting ◽  
Prevention And Treatment

BACKGROUND In the emergency situation of COVID-19, off-label therapies and newly developed vaccines may bring the patients adverse drug event (ADE) risks. Data mining based on spontaneous reporting systems (SRSs) is a promising and efficient way to detect potential ADEs so as to help health professionals and patients get rid of these risks. OBJECTIVE This pharmacovigilance study aimed to investigate the ADEs of “Hot Drugs” in COVID-19 prevention and treatment based on the data of the US Food and Drug Administration (FDA) adverse event reporting system (FAERS). METHODS FAERS ADE reports associated with COVID-19 from the 2nd quarter of 2020 to the 2nd quarter of 2021 were retrieved with “Hot Drugs” and frequent ADEs recognized. A combination of support, proportional reporting ratio (PRR) and Chi-square (2) test was applied to detect significant “Hot Drug” & ADE signals by Python programming language on Jupyter notebook. RESULTS 13,178 COVID-19 cases were retrieved with 18 “Hot Drugs” and 312 frequent ADEs on “Preferred Term” (PT) level. 18  312 = 5,616 “Drug & ADE” candidates were formed for further data mining. The algorithm finally produced 219 significant ADE signals associated with 17 “Hot Drugs”and 124 ADEs.Some unexpected ADE signals were observed for chloroquine, ritonavir, tocilizumab, Oxford/AstraZeneca COVID-19 Vaccine and Moderna COVID-19 Vaccine. CONCLUSIONS Data mining is a promising and efficient way to assist pharmacovigilance work and the result of this paper could help timely recognize ADEs in the prevention and treatment of COVID-19.

No association between proton pump inhibitor use and dementia risk: data mining of US Food and Drug Administration adverse event reporting system

2021 ◽  
Author(s):  
Bin Wu ◽  
Qiaozhi Hu ◽  
Fangyuan Tian ◽  
Fengbo Wu ◽  
Yuwen Li ◽  
...  
Keyword(s):  
Data Mining ◽  
Adverse Event ◽  
Proton Pump ◽  
Reporting System ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Reporting Odds Ratio ◽  
Event Reporting ◽  
Long Duration ◽  
Dementia Risk

Abstract Proton pump inhibitors (PPIs) were widely used around the world. Studies suggested conflicting results between PPIs treatment and the risk of dementia. This study examined the association between six PPIs and dementia risk by mining the US FDA Adverse Event Reporting System (FAERS) database from 2004 to 2019. We employed reporting odds ratio (ROR) and proportional reporting ratio (PRR) to detect the signals of dementia relevant to PPIs. We also analyzed characteristics of PPI reports, compared dementia events between short- and long- duration PPIs treatment. Finally, we identified 2104 dementia cases with PPIs treatment. We did not detect significant signals between PPIs and dementia, ROR = 0.99, 95%CI 0.94–1.03, PRR = 0.99, 95%CI 0.95–1.03, even in gastroesophageal reflux disease cases ROR = 0.65, 95%CI 0.58–0.73, PRR = 0.67, 95%CI 0.60–0.74. No significant differences of dementia events were detected between short- and long- duration groups, the OR (95%CI) of the 6 months, 1 year, 3 years and 5 years comparison were 0.85 (0.68–1.06), 0.92 (0.71–1.18), 0.81 (0.57–1.15) and 0.79 (0.52–1.22), respectively. Based on the current FAERS data mining, we discovered no association between PPIs use and the risk of dementia.

scholarly journals Thrombocytopenia with Tedizolid and Linezolid

2017 ◽  
Vol 62 (1) ◽  
Author(s):  
Erica Yookyung Lee ◽  
Aisling R. Caffrey
Keyword(s):  
Adverse Event ◽  
Confidence Interval ◽  
Drug Administration ◽  
Odds Ratio ◽  
Reporting System ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Reporting Odds Ratio ◽  
Event Reporting ◽  
Using Data

ABSTRACT Several studies have suggested the risk of thrombocytopenia with tedizolid, a second-in-class oxazolidinone antibiotic (approved June 2014), is less than that observed with linezolid (first-in-class oxazolidinone). Using data from the Food and Drug Administration adverse event reporting system (July 2014 through December 2016), we observed significantly increased risks of thrombocytopenia of similar magnitudes with both antibiotics: linezolid reporting odds ratio [ROR], 37.9 (95% confidence interval [CI], 20.78 to 69.17); tedizolid ROR, 34.0 (95% CI, 4.67 to 247.30).

Using Data Mining to Predict Safety Actions from FDA Adverse Event Reporting System Data

2007 ◽  
Vol 41 (5) ◽  
pp. 633-643 ◽  
Author(s):  
Alan M. Hochberg ◽  
Stephanie J. Reisinger ◽  
Ronald K. Pearson ◽  
Donald J. O’Hara ◽  
Kevin Hall
Keyword(s):  
Data Mining ◽  
Adverse Event ◽  
Reporting System ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Event Reporting ◽  
System Data ◽  
Using Data

scholarly journals Comparison of Quetiapine Abuse and Misuse Reports to the FDA Adverse Event Reporting System With Other Second-Generation Antipsychotics

2019 ◽  
Vol 13 ◽  
pp. 117822181984420 ◽  
Author(s):  
Kirk E Evoy ◽  
Chengwen Teng ◽  
Victor G Encarnacion ◽  
Brian Frescas ◽  
John Hakim ◽  
...  
Keyword(s):  
Adverse Event ◽  
Second Generation ◽  
Reporting System ◽  
Proportional Reporting Ratio ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Abuse Potential ◽  
Mortality Data ◽  
Event Reporting ◽  
Second Generation Antipsychotics

Background: Second-generation antipsychotics (SGAs) are assumed to have little abuse potential. However, reports of quetiapine abuse have emerged as prescribing has increased in recent years. The US Food and Drug Administration’s (FDA) Adverse Event Reporting System (FAERS) provides postmarketing information regarding adverse drug events (ADEs). This is the first study to analyze quetiapine abuse-related ADEs reported to FAERS to determine whether a disproportionate rate of such events have been reported when compared with other commonly used SGAs. Methods: A cross-sectional analysis of FAERS data from January 1, 2015, to December 31, 2017, was performed. The total number of all-cause and abuse-related ADEs reported to FAERS regarding quetiapine, olanzapine, aripiprazole, and risperidone were identified, along with demographic and mortality data. The proportional reporting ratio (PRR) was calculated to assess disproportionate reporting of abuse-related adverse drug reactions between quetiapine and each of three alternative SGA medications. Results: Abuse-related ADEs represented 11% (3144/27 962) of total ADEs reported for quetiapine, 8% for olanzapine (1548/19 228), 5% (1380/29 699) for aripiprazole, and 3% (1168/45 518) for risperidone. The PRRs (95% confidence interval) for quetiapine versus olanzapine, aripiprazole, and risperidone were 1.40 (1.32-1.48), 2.42 (2.28-2.57), and 4.38 (4.10-4.68), respectively, indicating that abuse-related events were significantly more likely to be reported with quetiapine than each comparator drug. In addition, more deaths were reported among the abuse-related events regarding quetiapine (673) than olanzapine (200), aripiprazole (88), and risperidone (143). Conclusion: This study corroborates recent evidence indicating that quetiapine might possess a significantly higher abuse potential than other commonly used SGAs. Although prospective studies are needed to better understand the abuse potential of quetiapine, increased vigilance in monitoring for signs of substance abuse might be warranted when prescribing quetiapine.

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