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Using PMDA Drug Adverse Event Report Database, Study on Collective Background of Adverse Events Caused by the Total Cold Medicine : Classification of Onset Cases Using Latent Class Analysis / 薬剤疫学
Japanese Journal of Pharmacoepidemiology ; : 75-87, 2018.
Article in Japanese | WPRIM | ID: wpr-688485
ABSTRACT
Objective: Using PMDA's medication side effect database (JADER), the aim of this study is to explore the collective background and characteristics of cases in which adverse events were caused by the total cold medicine.MethodsLatent class analysis is performed on 990 subject cases reported from April 2004 to June 2015. The target group is classified into plural, and each characteristic is clearly indicated. Furthermore, the number of adverse events is counted for each class, and specialization coefficients are calculated. In addition, the signal detection is performed with the same data.Results:The population was divided into three classes. Class 1 was a group which do not have the original disease or medication, 53.7% of the whole, and it was set as “health group” . Adverse events specialized were immune system diseases. Class 2 was 33.2%, a positive group for self-treatment, it was set as “self-treatment oriented group” . A specialized adverse event was a serious skin disorder. Class 3 was 13.1%, and 90% of the class was over 60 years old and almost people had primary diseases and medicines, so they were “high age outpatient treatment group” . The main adverse events were lung disease and nervous system disorder. It was possible to relate the characteristic of the group as a background factor.Conclusion:By applying Latent class analysis to the adverse event, it was possible to clarify the relationship between the occurrence of adverse event and its background.This research is applicable to other medicines, and expected to contribute as a new application method of JADER.

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Index: WPRIM (Western Pacific) Language: Japanese Journal: Japanese Journal of Pharmacoepidemiology Year: 2018 Type: Article

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Index: WPRIM (Western Pacific) Language: Japanese Journal: Japanese Journal of Pharmacoepidemiology Year: 2018 Type: Article