• Korean Journal of Clinical Pharmacy
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• v.33 no.2
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• pp.86-96
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• 2023

Background: Using KIDS-KAERS database (KIDS-KD) from 2016 to 2020, the aim is to investigate signals of adverse events of alpha-adrenoceptor antagonists and to present adverse events that are not included in the precautions for use when marketing approval. Methods: This study was conducted by disproportionality analysis. Data mining analysis was performed to detect signals of alpha-adrenoceptor antagonists, such as terazosin, doxazosin, alfuzosin, silodosin, and tamsulosin. The signal was defined by three criteria as proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC). Detected signals were compared with product labeling and the European Medicines Agency-Important Medical Events list. Results: Out of the total number of 408,077 reports for adverse events, 6,750 cases were reported as adverse events of alpha-adrenoceptor antagonists. Dizziness, mouth dryness, hypotension postural, and oedema peripheral are identified as common adverse events of five alpha-adrenoceptor antagonists and are typically listed on drug labels. However, new signals were detected for pneumonia, chronic obstructive airway disease, eye diseases such as glaucoma and cataracts, fracture, and ileus of tamsulosin that were not previously listed on the drug labels in Korea. Conclusions: This study identified signals related to adverse drug reactions of alpha-adrenoceptor antagonists and presented serious adverse events, suggesting new adverse reactions to be aware of when using alpha-adrenoceptor antagonists.

• Korean Journal of Clinical Pharmacy
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• v.27 no.4
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• pp.221-227
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• 2017

Background: As personalized healthcare industry has attracted much attention, big data analysis of healthcare data is essential. Lots of healthcare data such as product labeling, biomedical literature and social media data are unstructured, extracting meaningful information from the unstructured text data are becoming important. In particular, text mining for adverse drug reactions (ADRs) reports is able to provide signal information to predict and detect adverse drug reactions. There has been no study on text analysis of expert opinion on Korea Adverse Event Reporting System (KAERS) databases in Korea. Methods: Expert opinion text of KAERS database provided by Korea Institute of Drug Safety & Risk Management (KIDS-KD) are analyzed. To understand the whole text, word frequency analysis are performed, and to look for important keywords from the text TF-IDF weight analysis are performed. Also, related keywords with the important keywords are presented by calculating correlation coefficient. Results: Among total 90,522 reports, 120 insulin ADR report and 858 tramadol ADR report were analyzed. The ADRs such as dizziness, headache, vomiting, dyspepsia, and shock were ranked in order in the insulin data, while the ADR symptoms such as vomiting, 어지러움, dizziness, dyspepsia and constipation were ranked in order in the tramadol data as the most frequently used keywords. Conclusion: Using text mining of the expert opinion in KIDS-KD, frequently mentioned ADRs and medications are easily recovered. Text mining in ADRs research is able to play an important role in detecting signal information and prediction of ADRs.

• Korean Journal of Clinical Pharmacy
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• v.33 no.2
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• pp.122-127
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• 2023

Background: This study was aimed to identify the safety signals of metoclopramide in Korea Adverse Event Reporting System (KAERS) database by proportionality analysis methods. Methods: The study was conducted using Korea Institute of Drug Safety and Risk Management-Korea Adverse Event Reporting System Database (KIDS-KD) reported from January 2013 to December 2017 through KAERS. Signals of metoclopramide that satisfied the data-mining indices of proportional reporting ratio (PRR), reporting odds ratio (ROR) and information component (IC) were defined. The detected signals were checked whether they included in drug labels in the Ministry of Food and Drug Safety (MFDS), U.S. Food and Drug Administration (FDA) and Micromedex^®. Results: A total number of drug AE reports associated with all drugs of data in this study was 2,665,429. Among them, the number of AE reports associated with metoclopramide was 22,583. Forty-two meaningful signals of metoclopramide were detected that satisfied with the criteria of data-mining indicies. Especially neurological signals including extrapyramidal reactions, represented in the safety letter of regulatory agencies were identified in this study. Conclusion: Neurological signals of metoclopramide including extrapyramidal reactions were detected. It is believed that this search for signals can contribute to ensuring safety in the use of metoclopramide.