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자발적 부작용보고자료를 이용한 의약품 상호작용 실마리 정보 탐색 방법
원희현,조해린,최현영,최남경 한국보건정보통계학회 2024 보건정보통계학회지 Vol.49 No.1
. Statistical methodologies of signal detection for drug-drug interactions (DDIs) have been developed and used. In this study, we review methodologies for DDI signal detection using the spontaneous reporting system. We describe the characteristics of the additive and multiplicative risk model, logistic regression model, Multi-item Gamma-Poisson Shrinker, Ω shrinkage measure model, and Chi-square statistics model. We discuss the advantages and disadvantages of each methodology along with examples, providing researchers with information to choose the most appropriate methodology for their study.
의약품부작용보고원시자료를 활용한 와파린과 스타틴 동시복용의 약물 상호작용 실마리정보 탐색
원희현(Heehyun Won),최현영(HyunYoung Choi),박수빈(Suvin Park),최남경(Nam-Kyong Choi) 대한약학회 2023 약학회지 Vol.67 No.1
The increase in polypharmacy in elderly patients is recognized as a serious health, economic, and social problem. Warfarin and statins are commonly co-administered to cardiovascular disease patients. However, there is a potential risk of drug-drug interaction (DDI). The objective of this study was to detect signals of adverse events (AEs) for DDI after concomitant use of warfarin and statins using Korea adverse events reporting system (KAERS) database. KAERS database from January 2016 to December 2020 was used. Omega (Ω) shrinkage measure model and Chi-square statistics model were used to calculate the criteria for detecting AEs signal resulting from concomitant use of warfarin and statins. Three indices were used to define signals: Ω025 (frequentist) >0, Ω025 (Bayesian) >0, and >2. Detected signals were compared with AEs listed on the drug label in Korea, Micromedex, and SIDER for warfarin and statins, respectively. Twenty-seven AEs on reports of concomitant use were detected as signals. Of 27 detected signals, 11 signals, including breath odour not otherwise specified (NOS), depersonalization, gastrointestinal neoplasm NOS, pleural effusion, medical device complication, menopausal symptoms, oedema cerebral, osteitis, prostatic hyperplasia, lipoma, and skin hypertrophy, were not listed on drug label. We identified signals for concomitant use of warfarin and statins. Careful monitoring and further pharmacoepidemiological studies of DDI associated with new signals using other databases are needed.
미국과 유럽의 코로나19 백신 안전성 모니터링을 위한 특별 관심 대상의 이상사례
임은선,최현영,원희현,박수빈,이희언,조해린,정나영,이중엽,최남경 한국보건사회약료경영학회 2021 한국보건사회약료경영학회지 Vol.9 No.1
Since the outbreak of the Covid-19 pandemic, multinational pharmaceutical companies have accelerated vaccine development at an unprecedentedly rapid pace. The safety concerns about Covid-19 vaccines may lead to the increasing number of people with vaccine distrust, making it difficult to maintain the vaccination rate for obtaining herd immunity. Therefore, some countries, including the United States (US) and Europe, have selected adverse event of special interests (AESIs) and planned to conduct vaccine safety monitoring. In the US, the vaccine passive surveillance systems such as Vaccine Adverse Event Reporting System (VAERS) and the active surveillance systems, including the Biologics Effectiveness and Safety (BEST) Initiative and Vaccine Safety Datalink (VSD) have selected AESIs for COVID-19 vaccines. In Europe, the Safety Platform for Emergency vACcines (SPEAC) project and the vACCine Covid-19 monitoring readinESS (ACCESS) project have selected AESIs, respectively. We confirmed the number of VAERS, BEST, VSD, SPEAC, and ACCESS AESIs, respectively 16, 15, 20, 34, and 38. We identified among the 52 AESIs included in the US and Europe that were commonly contained anaphylaxis, Guillain-Barre syndrome (GBS), myopericarditis/ myocarditis/ pericarditis, multisystem inflammatory syndrome (MIS) and stroke. This paper identified the backgrounds and characteristics of AESIs for COVID-19 vaccines in the US and Europe.
국내 건강보험 청구자료의 활용 촉진을 위한 현안 및 개선방안
최남경,김희진,김동욱,김명규,김미숙,배승진,정선영,김예지,김정아,박수빈,조해린,신애선,신주영,안성복,안정훈,양보람,원희현,이승미,이희언,이중엽 대한약물역학위해관리학회 2024 약물역학위해관리학회지 Vol.16 No.1
While health insurance claims data in Korea have the potential as evidence for drug regulatory decision-making, its effective utilization remains limited. This study aims to identify the challenges encountered by researchers in utilizing claims data and discuss improvement strategies. We summarized practical difficulties encountered by researchers who have experience using claims data from the National Health Insurance Service and the Health Insurance Review and Assessment Service. Challenges encountered by researchers included difficulties in acquiring drug data, delays in data provision, limited provision of information on specific conditions, drugs, and treatments, small data capacity, short data usage periods, and spatiotemporal considerations when accessing data. To maximize the utility of claims data in drug regulatory decision-making, continuous communication between researchers and data providers is necessary for addressing these challenges. (PeRM 2024;16:1-10)