scholarly journals A Computational Framework for Identifying Age Risks in Drug-Adverse Event Pairs

2022 ◽  
Author(s):  
Zhizhen Zhao ◽  
Ruoqi Liu ◽  
Lei Wang ◽  
Lang Li ◽  
Chi Song ◽  
...  
Keyword(s):  
Adverse Event ◽  
Adverse Drug Events ◽  
Case Reports ◽  
Adverse Event Reporting System ◽  
Population Level ◽  
Individual Case ◽  
Risk Identification ◽  
Adverse Event Reporting ◽  
Computational Framework ◽  
Drug Adverse Event

The identification of associations between drugs and adverse drug events (ADEs) is crucial for drug safety surveillance. An increasing number of studies have revealed that children and seniors are susceptible to ADEs at the population level. However, the comprehensive explorations of age risks in drug-ADE pairs are still limited. The FDA Adverse Event Reporting System (FAERS) provides individual case reports, which can be used for quantifying different age risks. In this study, we developed a statistical computational framework to detect age group of patients who are susceptible to some ADEs after taking specific drugs. We adopted different Chi-squared tests and conducted disproportionality analysis to detect drug-ADE pairs with age differences. We analyzed 4,580,113 drug-ADE pairs in FAERS (2004 to 2018Q3) and identified 2,523 pairs with the highest age risk. Furthermore, we conducted a case study on statin-induced ADE in children and youth. The code and results are available at https://github.com/Zhizhen-Zhao/Age-Risk-Identification

scholarly journals Comparison of Rhabdomyolysis Associated With Sacubitril/valsartan-related Drug-drug Interactions by Individual Statins in an Adverse Event Reporting System

2021 ◽  
Author(s):  
Tomiko Sunaga ◽  
Ryo Yonezawa
Keyword(s):  
Adverse Event ◽  
Drug Interactions ◽  
Reporting System ◽  
Case Reports ◽  
Organic Anion ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Reporting Odds Ratio ◽  
Event Reporting ◽  
Structured Analysis

Abstract BackgroundSacubitril/valsartan was approved in Japan recently. Sacubitril is an inhibitor of organic anion-transporting polypeptide (OATP) 1B1 and 1B3. In Japan, sacubitril/valsartan product labeling indicates that it should be cautiously co-administered with atorvastatin due to drug-drug interactions (DDIs). However, all statins are the substrates of OATP1B1 and/or 1B3. Therefore, we should be cautious about DDIs between sacubitril/valsartan and all other statins.ObjectiveTo evaluate the association between rhabdomyolysis and concomitant association of sacubitril/valsartan with atorvastatin and all other statins.MethodsCase reports from the U.S. Food and Drug Administration’s Adverse Event Reporting System (FAERS) from 2015 to Q4/2020 were used. All FAERS reports on sacubitril/valsartan were captured through a structured analysis. We compared the proportion of cases reporting the adverse events associated with rhabdomyolysis and the concomitant use of sacubitril/valsartan and atorvastatin to those with sacubitril/valsartan and all other statins.ResultsAmong 10,940 case reports on sacubitril/valsartan, compared with all other drugs, statin users were associated with increased rhabdomyolysis (reporting odds ratio =4.54[2.62-7.87]). However, compared with all other statins, atorvastatin was not associated with increased rhabdomyolysis. ConclusionsWe suggest that the co-administration of sacubitril/valsartan with atorvastatin as well as other statins should be carefully managed as it may induce rhabdomyolysis.

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.

scholarly journals SAFETY SIGNAL DETECTION OF CARDIAC DISORDERS ADVERSE DRUG EVENTS FOR AZITHROMYCIN IN PEDIATRIC POPULATION USING HEALTH CANADA ADVERSE EVENT REPORTING SYSTEM DATABASE

2017 ◽  
Vol 9 (6) ◽  
pp. 80
Author(s):  
Gaurav Kumar Shah ◽  
Mukesh Kumar Patel ◽  
Dr. Bhanwarlal Jat
Keyword(s):  
Adverse Event ◽  
Adverse Drug Events ◽  
Reporting System ◽  
Pediatric Population ◽  
Adverse Event Reporting System ◽  
Cardiovascular Disorder ◽  
Paediatric Population ◽  
Adverse Event Reporting ◽  
Event Reporting ◽  
System Database

Objective: We conducted signal detection of adverse drug events reported in Health Canada adverse event reporting system database “MedEffect” for azithromycin, a macrolide derivative and the first azalide antimicrobial agent to review the cardiac disorders adverse drug events (ADEs) in pediatric population with the drug labels of selected countries including India, USA, UK, Canada, Switzerland, Australia, New Zealand.Methods: We extracted data between January 1965 and June 2016 from the Canada adverse event reporting system database “MedEffect”. Frequentist and Bayesian methods were used to calculate disproportionality distribution of drug-adverse event (AE) pairs. The AE which was detected by all the three indices of proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC) was identified as a potential signal. AE reports for azithromycin, among which 3651 reports were attributed to paediatrics.Results: The signal detected by PRR and ROR for tachycardia associated with azithromycin were found to be 1.3 and for cardiovascular disorder were 1.2. The IC for azithromycin by a Bayesian method was 0.3 for both, tachycardia and cardiovascular disorder. Both AEs of cardiovascular disorder and tachycardia were detected as potential signals of azithromycin for the paediatric population. Comparing drug labels of 7 countries in paediatric population, both adverse events were not listed on any of the labels of seven countries against the pediatric population.Conclusion: We detected 2 new potential signals of azithromycin which were not listed on the labels of 7 countries. Therefore, it should be accompanied by a signal evaluation including causal association, clinical significance, and preventability.

scholarly journals 2296. Hypoglycemia Risk with Antibiotics: An Epidemiologic Surveillance Study of the FDA Adverse Event Reporting System (FAERS)

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S787-S787
Author(s):  
Kaitlin E Kennedy ◽  
Chengwen Teng ◽  
Taylor M Patek ◽  
Christopher R Frei
Keyword(s):  
Adverse Event ◽  
Drug Safety ◽  
Potential Risk ◽  
Case Reports ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Event Reporting ◽  
Epidemiologic Surveillance ◽  
Safety Warning ◽  
Medical Dictionary

Abstract Background In July of 2018, the FDA published a drug safety warning for the potential risk of developing hypoglycemia with fluoroquinolones. Some studies have evaluated the potential risk of developing hypoglycemia with linezolid and tigecycline. A few case reports have also been published that report hypoglycemia from cefditoren, doxycycline, and trimethoprim-sulfamethoxazole use. Since data comparing various antibiotics and the risk of developing hypoglycemia is limited, the objective of this study was to evaluate the association between hypoglycemia and antibiotics using the FDA Adverse Event Reporting Systems (FAERS). Methods FAERS reports from January 1, 2004 to December 31, 2017 were included in the study. The Medical Dictionary for Regulatory Activities (MedDRA) was used to identify cases of hypoglycemia. Reporting odds ratios (RORs) and corresponding 95% confidence intervals (95% CI) for the association between antibiotics and hypoglycemia were calculated. An association was considered to be statistically significant when the lower limit of the 95% CI was greater than 1.0. Results A total of 2,334,959 reports (including 18,466 hypoglycemia reports) were considered, after inclusion criteria were applied. Cefditoren had the greatest proportion of hypoglycemia reports, representing 10% of all cefditoren reports. Statistically significant hypoglycemia RORs (95% CI) for antibiotics were: cefditoren 14.03 (8.93–22.03), tigecycline 3.32 (1.95–5.65), clarithromycin 2.41 (1.89–3.08), ertapenem 2.07 (1.14–3.75), moxifloxacin 2.06 (1.59–2.65), levofloxacin 1.66 (1.37–2.01), linezolid 1.54 (1.07–2.20). Conclusion Cefditoren, tigecycline, clarithromycin, ertapenem, moxifloxacin, levofloxacin, and linezolid were all significantly associated with hypoglycemia. The ertapenem association had not been reported in prior literature. Levofloxacin and moxifloxacin were the only fluoroquinolones significantly associated with hypoglycemia, even though the FDA drug safety warning was issued for all fluoroquinolones. Doxycycline and trimethoprim-sulfamethoxazole were not significantly associated with hypoglycemia, even though case reports have reported hypoglycemia with doxycycline and trimethoprim-sulfamethoxazole. Disclosures All authors: No reported disclosures.

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