Application of FDA Adverse Event Report Data to the Surveillance of Dietary Botanical Supplements

2008 ◽  
Vol 42 (5) ◽  
pp. 653-660 ◽  
Author(s):  
Robert B Wallace ◽  
Brian M Gryzlak ◽  
M Bridget Zimmerman ◽  
Nicole L Nisly

Background: Concerns have been raised about the sufficiency of dietary botanical supplement (DBS) surveillance in the US. The Food and Drug Administration's Center for Food Safety and Applied Nutrition's Adverse Event Reporting System (CAERS) represents one of the few existing surveillance mechanisms, but it has not been well characterized with respect to DBS adverse effects. Objective: To characterize data on DBSs associated with adverse event reports submitted to CAERS. Methods: We requested and obtained CAERS data from 1999 to 2003 involving adverse effects associated with the 6 most frequently used DBSs: Echinacea, ginseng, garlic, Ginkgo biloba, St. John's wort, and peppermint. We summarized and characterized the adverse event reports received, focusing on the composition of the DBSs and the nature of associated adverse events. We also cross-referenced reported single-ingredient DBSs with corresponding available product information. A sample of CAERS cases associated with signal DBSs was also characterized in detail. Results: CAERS reports involving ginseng DBSs were most frequently reported during the study period, whereas reports involving St. John's wort were the least frequently reported. Most CAERS reports involved multiple-ingredient DBSs, and 3-13% of reports involved multiple DBSs. Gastrointestinal and neurologic problems were the most common clinical outcomes among single-ingredient DBS-associated adverse events. Conclusions: CAERS surveillance of DBS adverse effects is potentially as effective as other passive surveillance methods, but the number of reports is relatively small, validation is incomplete, and some inconsistencies within reports were found. Reports in CAERS may underrepresent DBS adverse events associated with DBS consumption.

Author(s):  
Xiang Zhou ◽  
Xiaofei Ye ◽  
Yinghong Zhai ◽  
Fangyuan Hu ◽  
Yongqing Gao ◽  
...  

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.


2019 ◽  
Vol 14 (1) ◽  
pp. 21-26 ◽  
Author(s):  
Viswam Subeesh ◽  
Eswaran Maheswari ◽  
Hemendra Singh ◽  
Thomas Elsa Beulah ◽  
Ann Mary Swaroop

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.


Vaccine ◽  
2019 ◽  
Vol 37 (44) ◽  
pp. 6760-6767 ◽  
Author(s):  
Michael M. McNeil ◽  
Iwona Paradowska-Stankiewicz ◽  
Elaine R. Miller ◽  
Paige L. Marquez ◽  
Srihari Seshadri ◽  
...  

2018 ◽  
Vol 268 ◽  
pp. 441-446 ◽  
Author(s):  
Yoon Kyong Lee ◽  
Jung Su Shin ◽  
Youngwon Kim ◽  
Jae Hyun Kim ◽  
Yun-Kyoung Song ◽  
...  

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