Detecting Signals of Dietary Supplement Adverse Events from the CFSAN Adverse Event Reporting System (CAERS).
Jake Vasilakesa b c, Rubina Fatima Rizvia b, Jianqiu Zhanga c, Terrence J Adama b, Zhang Ruia b
- aInstitute for Health Informatics, University of Minnesota, Minneapolis, MN, USA
- bCollege of Pharmacy, University of Minnesota, Minneapolis, MN, USA
- cInstitute for Health Informatics, University of Minnesota,,,Minneapolis,MN,USA
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Abstract
Dietary supplement adverse events are potentially severe, yet knowledge regarding the safety of dietary supplements is limited. The CFSAN Adverse Event Reporting System (CAERS) contains records of adverse events attributed to supplements and is potentially useful for dietary supplement pharmacovigilance. This study investigates the feasibility of mining CAERS for dietary supplement adverse events as well as for monitoring the safety of dietary supplement products. Using three online resources, we mapped products in CAERS to their listed ingredients. We then ran four standard signal detection algorithms over the ingredient-adverse event and product-adverse event pairs extracted from CAERS and ranked the detected associations. Comparing 130 signals detected by all four algorithms with a dietary supplement resource, we found evidence for 73 (56%) associations. In addition, some detected product-adverse event signals were consistent with product safety information. We have made a database of the detected adverse events publicly available at https://github.com/zhang-informatics/DDSAE.
TL;DRThis study investigates the feasibility of mining CAERS for dietary supplement adverse events as well as for monitoring the safety of dietary supplement products. (Semantic Scholar)