Association Patterns in Open Data to Explore XXXX Adverse Events.

@entity1 @entity146 @entity294 @entity2348 @entity2177 @entity148 @entity158
BACKGROUND: @entity2177 is one of the main drugs to treat @entity2348 . @entity2348 can lead to high morbidity, mortality, and costs of treatment in the world. In this study, an analysis was conducted using the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (AERS) database on the adverse events of @entity2177 . OBJECTIVES: The aim of this study was to explore unknown associations among the adverse events of @entity2177 , @entity1 demographics and adverse event outcomes. METHODS: A search of FDA AERS reports was performed and some statistics was highlighted. The most frequent adverse events and event outcomes of @entity2177 were listed, age and gender specific distribution of adverse events are reported, then the apriori algorithm was applied to the dataset to obtain some association rules and objective measures were used to select interesting ones. Furthermore, the results were compared against classical data mining algorithms and discussed. RESULTS: The search resulted in 6 531 reports. The reports included within the dataset consist of 3 585 (55.8%) female and 2 884 (44.1%) male @entity1 . The mean age of @entity1 is 54.59 years. Preschool @entity1 , middle aged and aged groups have most adverse events reports in all groups. Pyrexia has the highest frequency with @entity2177 , followed by @entity158 , @entity294 , and @entity148 in this order and the most frequent adverse event outcome is hospitalization. Age and gender based differences in the events in @entity1 were found. In addition, some of the interesting associations obtained from the Apriori algorithm include not only @entity146 but specifically their manifestation in specific gender groups. CONCLUSIONS: The FDA AERS offers an important data resource to identify new or unknown adverse events of drugs in the biomedical domain. The results that were obtained in this study can provide valuable information for medical researchers and decision makers at the pharmaceutical research field.
