Baek, Ji-Won;Yang, Bo Ram;Choi, Subin;Shin, Kwang-Hee
Korean Journal of Clinical Pharmacy
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v.31
no.4
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pp.324-331
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2021
To investigate signals of adverse drug reactions of finasteride by using the Korea Adverse Events Reporting System (KAERS) database. This pharmacovigilance was based on the database of the drug-related adverse reactions reported spontaneously to the KAERS from 2013 to 2017. This study was conducted by disproportionality analysis. Data mining analysis was performed to detect signals of finasteride. The signal was defined by three criteria as proportional reporting ratio (PRR), reporting odds ratio (ROR), and information component (IC). The signals of finasteride were compared with those of the other drugs; dutasteride (similar mechanism of action), minoxidil (different mechanism but similar indications for alopecia), silodosin (different mechanism but similar indications for BPH). It was examined whether the detected signals exist in drug labels in Korea. The total number of adverse event-drug pairs was reported 2,665,429 from 2013 to 2017, of which 1,426 were associated with finasteride. The number of investigated signals of finasteride was 42. The signals that did not include in the drug label were 29 signals, including mouth dry, hypotension, dysuria etc. The signal of finasteride was similar to that of dutasteride and silodosin but was different to that of minoxidil. Early detection of signals through pharmacovigilance is important to patient safety. We investigated 29 signals of finasteride that do not exist in drug labels in Korea. Further pharmacoepidemiological studies should be needed to evaluate the signal causality with finasteride.
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.
Background: 3-Hydroxy-3-methylglutaryl coenzyme A reductase inhibitors (statins) effectively reduce serum levels of low-density lipoprotein (LDL) and total cholesterol. High-intensity statins are recommended for all patients aged ${\leq}75$ with clinical atherosclerotic cardiovascular disease (ASCVD), diabetes mellitus aged 40-75 with ${\geq}7.5%$ estimated 10-year ASCVD risk and LDL-C ${\geq}190mg/dL$. High-intensity statins associated with more frequent adverse events (AEs) compared to moderate- to low-intensity statins. The aim of this study was to compare AEs between high-intensity and moderate- to low-intensity statin group using the Korea Adverse Event Reporting System (KAERS) database. Methods: Adults (${\geq}18years$) with statin-associated AEs from July 2009-June 2014 were included. Only AEs classified as "certain", "probable" and "possible" based on the WHO-Uppsala Monitoring Center criteria were analyzed. Results: In total, 247 AEs from 196 patients [high-intensity statin group (HG), n = 25 (13%); moderate- to low-intensity statin group (MLG), n = 171 (87%)] were included. Mean age was higher in HG compared with MLG ($67{\pm}14$ vs $62{\pm}12$). The HG showed a significant higher frequency of liver/biliary system disorders (37% vs 14%, p = 0.001). Hepatic function abnormal was reported more frequently in HG compared to MLG (26% vs 9%, p = 0.006). Conclusion: According to KAERS data, liver/biliary system disorders were more frequently reported in HG compared to MLG.
Hyunji Koo;Jun Young Kwon;Jae-Hyuk Choi;Seung Hun You;Sewon Park;Kyeong Hye Jeong;Sun-Young Jung
Korean Journal of Clinical Pharmacy
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v.33
no.2
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pp.86-96
/
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.
Background: Monoclonal antibodies for the treatment of patients with different types of cancer, such as cetuximab, have been widely used for the past 10 years in oncology. Although drug information package insert contains some representative adverse events which were observed in the clinical trials for drug approval, the overall adverse event patterns on the real-world cetuximab use were less investigated. Also, there have been no published papers that deal with the full spectrums of adverse drug events of cetuximab using national-wide drug safety surveillance systems. Methods: In this study, we detected new adverse event signals of cetuximab in the Korea Adverse Event Reporting System (KAERS) by utilizing proportional reporting ratios, reporting odds ratios, and information components indices. Results: The KAERS database included 869,819 spontaneous adverse event reports, among which 2,116 reports contained cetuximab. We compared the labels of cetuximab among the United States, European Union, Australia, Japan, and Korea to compare the current labeling information and newly detected signals of our study. Some of the signals including hyperkeratosis, tenesmus, folliculitis, esophagitis, neuralgia, disseminated intravascular coagulopathy, and skin/throat tightness were not labeled in the five countries. Conclusion: We identified new signals that were not known at the time of market approval.
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.
Hyejung Pyo;Tae Young Kim;Su Been Choi;Hyeong Jun Jo;Hae Lee Kang;Jung Sun Kim;Hye Sun Gwak;Ji Min Han
Korean Journal of Clinical Pharmacy
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v.34
no.2
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pp.100-107
/
2024
Background: The purpose of this study was to detect signals of adverse events (AEs) of DPP-IV inhibitors using the KIDs-Korea Adverse Event Reporting System (KAERS) database. Methods: This study was conducted using AEs reported from January 2009 to December 2018 in the KIDs-KAERS database. For signal detection, disproportionality analysis was performed. Signals of DPP-IV inhibitor that satisfied the data-mining indices of reporting odds ratio (ROR) were detected. Results: Among the total number of 10,364 AEs to all oral hypoglycemic agents, the number of reported AEs related to DPP-IV inhibitors was 1,674. Analysis of reported AEs of DPP-IV inhibitors at the SOC levels showed that Respiratory system disorders were the highest at 4.31 (95% CI 3.01-6.17), followed by Skin and appendages disorders at 2.04 (95% CI 1.74-2.38). When analyzing AEs reported at the PT level, pharyngitis was the highest at 73.90 (95% CI 17.59-310.49), followed by arthralgia at 6.08 (95% CI 2.04-18.11), and coughing at 5.21 (95% CI 2.07-13.15). Conclusions: Based on the result of the study, deeper consideration is required according to the characteristics of the patients in prescribing DPP-IV inhibitors among oral hypoglycemic agents, and continuous monitoring of the occurrence of related Adverse Drug Reactions during administration is also required.
Objectives: Tonifying herbal medicines are used to nourish and balance the body's qi, blood, yin, and yang, targeting deficiencies. They are the second most frequently used category by consumers visiting Korean medicine clinics, following prescriptions for back pain. This study aimed to analyze the adverse events associated with herbal medicine products classified as tonics through a national pharmacovigilance database. Methods: We investigated 11 types of tonifying herbal medicine products (466 product codes) in the Korea Adverse Event Reporting System (KAERS) database from 2012 to 2021. Extracted adverse event reports were analyzed based on information of reports, patient demographics, classification of adverse events, reported herbal medicine products, and causality assessment results. Results: A total of 31 individual case safety reports were identified, covering 33 adverse events. The annual number of reports has increased over the study period. Most reports were filed by physicians and pharmacists, with the majority of patients being adults or elderly. Gastrointestinal disorders were the most frequently reported adverse events, accounting for 48.5% of cases. Of the 33 adverse events, 93.9% were classified as non-serious, while 6.1% were classified as serious. The most frequently reported herbal medicine products were Bojungikgi-tang, Yukmijihwang-tang, and Palmijihwang-tang. Conclusions: Although the study found that adverse events associated with tonifying herbal medicine products are generally not serious, it highlights the importance of systematic monitoring and reporting. The findings underscore the need for improved adverse event reporting systems within traditional Korean medicine to ensure patient safety and guide future research.
Han, Ji Min;Heo, Kyu-Nam;Lee, Ah Young;Min, Sang il;Kim, Hyun Jee;Baek, Jin-Hee;Rho, Juhyun;Kim, Sue In;Kim, Ji yeon;Lee, Haewon;Cho, Eunju;Ah, Young-Mi;Lee, Ju-Yeun
Korean Journal of Clinical Pharmacy
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v.32
no.2
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pp.116-124
/
2022
Background: High-alert medications (HAMs) are medications that bear a heightened risk of causing significant patient harm if used in error. To facilitate safe use of HAMs, identifying specific HAM lists for clinical setting is necessary. We aimed to develop the national level HAM list for acute care setting. Methods: We used three-step process. First, we compiled the pre-existing lists referring HAMs. Second, we analyzed medication related incidents reported from national patient safety incident report data and adverse events indicating medication errors from the Korea Adverse Event Reporting System (KAERS). We also surveyed the assistant staffs to support patient safety tasks and pharmacist in charge of medication safety in acute care hospital. From findings from analysis and survey results we created additional candidate list of HAMs. Third, we derived the final list for HAMs in acute care settings through expert panel surveys. Results: From pre-existing HAM list, preliminary list consisting of 42 medication class/ingredients was derived. Eight assistant staff to support patient safety tasks and 39 pharmacists in charge of medication safety responded to the survey. Additional 44 medication were listed from national patient safety incident report data, KAERS data and common medications involved in prescribing errors and dispensing errors from survey data. A list of mandatory and optional HAMs consisting of 10 and 6 medication classes, respectively, was developed by consensus of the expert group. Conclusion: We developed national level HAM list for Korean acute care setting from pre-existing lists, analyzing medication error data, survey and expert panel consensus.
Kim, Myo-Song;You, Seung-Hun;Park, Hye Min;Lee, Min-Taek;Kang, Ye-Jin;Koo, Hyunji;Jung, Sun-Young
Korean Journal of Clinical Pharmacy
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v.30
no.1
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pp.19-30
/
2020
Objective: To describe patterns of spontaneous reporting on adverse events following immunization (AEFIs) using the human papilloma virus (HPV) vaccine according to the Brighton Collaboration (BC) criteria. Methods: We used the Korea Adverse Event Reporting System (KAERS) database including vaccinations between 2008 and 2017. To apply BC criteria, we classified 58 BC AEFIs into World Health Organization Adverse Reaction Terminology (WHO-ART) codes. We applied MedDRA standard medical queries that were pre-defined as five BC AEFIs. Terminology mapping between MedDRA and WHO-ART terms was performed by three researchers. Descriptive statistics of individual case safety reports were analyzed according to BC applicability. Disproportionality analyses were performed on each BC AEFI and each preferred AEFI term according to the case-noncase approach; reporting odds ratio (ROR) and 95% confidence intervals (CI) were calculated. Results: Among the 30,266 reports of vaccinations between 2008 and 2017, 2,845 reports included the HPV vaccine. Of these reports, 1,511 (53.1%) included at least one BC AEFI. Reports from physicians or manufacturers included more BC AEFIs than from other reporters. Injection site reactions and fever were frequently reported in BC AEFIs; spontaneous abortion and ectopic pregnancy (ROR, 14.29 [95% CI, 4.30-47.49]) and vasculitic peripheral neuropathy (ROR, 8.57 [95% CI, 2.61-28.10]) showed the highest ROR. Among non-BC AEFIs, dizziness or myalgia were frequently reported; exposure during pregnancy (ROR, 23.95 [95% CI, 16.27-35.25]) and inappropriate schedule of administration (ROR, 22.89 [95% CI, 16.74-31.31]) showed the highest ROR. Conclusion: BC criteria would be applicable for labeled AEFIs, whereas analyzing non-BC AEFIs would be useful for detecting unlabeled AEFIs.
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