1.Pharmacodynamic Drug-Drug Interactions Considered to be Added in the List of Contraindications with Pharmacological Classification in Korea.
Nam Kyung JE ; Dong Sook KIM ; Grace Juyun KIM ; Sukhyang LEE
Korean Journal of Clinical Pharmacy 2015;25(2):120-128
OBJECTIVES: Drug utilization review program in Korea has provided 'drug combinations to avoid DCA)' alerts to physicians and pharmacists to prevent potential adverse drug events or inappropriate drug use. Seven hundred and six DCA pairs have been announced officially by the Ministry of Food and Drug Safety (MFDS) by March, 2015. Some DCA pairs could be grouped based on the drug interaction mechanism and its consequences. This study aimed to investigate the drug-drug interaction (DDI) pairs, which may be potential DCAs, generated by the drug class-drug class interaction method METHODS: Eleven additive/synergistic and one antagonistic drug class-drug class interaction groups were identified. By combining drugs of two interacting drug class groups, numerous DDI pairs were made. The status and severity of DDI pairs were examined using Lexicomp and Micromedex. Also, the DCA listing rate was calculated. RESULTS: Among 258 DDI pairs generated by the drug class-drug class interaction method, only 142 pairs were identified as official DCA pairs by the MFDS. One hundred and four pairs were identified as potential DCA pairs to be listed. QT prolonging agents-QT prolonging agents, triptans-ergot alkaloids, tricyclic antidepressants-monoamine oxidase inhibitors, and dopamine agonists-dopamine antagonists were identified as drug class-drug class interaction groups which have less than 50 % DCA listing rate. CONCLUSION: To improve the clinicians' adaptability to DCA alerts, the list of DCA pairs needs to be continuously updated.
Alkaloids
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Classification*
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Dopamine
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Drug Interactions
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Drug Utilization Review
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Drug-Related Side Effects and Adverse Reactions
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Humans
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Korea*
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Oxidoreductases
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Pharmacists
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Pharmacokinetics
2.Correlation between Drug Market Withdrawals and Socioeconomic, Health, and Welfare Indicators Worldwide.
Kye Hwa LEE ; Grace Juyun KIM ; Ju Han KIM
Journal of Korean Medical Science 2015;30(11):1567-1576
The relationship between the number of withdrawn/restricted drugs and socioeconomic, health, and welfare indicators were investigated in a comprehensive review of drug regulation information in the United Nations (UN) countries. A total of of 362 drugs were withdrawn and 248 were restricted during 1950-2010, corresponding to rates of 12.02+/-13.07 and 5.77+/-8.69 (mean+/-SD), respectively, among 94 UN countries. A socioeconomic, health, and welfare analysis was performed for 33 OECD countries for which data were available regarding withdrawn/restricted drugs. The gross domestic product (GDP) per capita, GDP per hour worked, health expenditure per GDP, and elderly population rate were positively correlated with the numbers of withdrawn and restricted drugs (P<0.05), while the out-of-pocket health expenditure payment rate was negatively correlated. The number of restricted drugs was also correlated with the rate of drug-related deaths (P<0.05). The World Bank data cross-validated the findings of 33 OECD countries. The lists of withdrawn/restricted drugs showed markedly poor international agreement between them (Fleiss's kappa=-0.114). Twenty-seven drugs that had been withdrawn internationally by manufacturers are still available in some countries. The wide variation in the numbers of drug withdrawals and restrictions among countries indicates the need to improve drug surveillance systems and regulatory communication networks.
Adolescent
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Adult
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Aged
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Child
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Child, Preschool
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Drug Utilization/*economics/statistics & numerical data
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Female
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Gross Domestic Product/*statistics & numerical data
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*Health Status Indicators
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Humans
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Infant
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Infant, Newborn
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Internationality
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*Life Expectancy
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Male
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Middle Aged
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Product Surveillance, Postmarketing/*economics/statistics & numerical data
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Safety-Based Drug Withdrawals/*economics/statistics & numerical data
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Social Welfare/economics/statistics & numerical data
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Socioeconomic Factors
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Statistics as Topic
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Young Adult