Журнал фармаконадзора

Абстрактный

Quantitative Pharmacovigilance Modeling for TCM Injections Adverse Event Reporting

Xiang Yongyang, Yi Danhui and Xie Mingyan

For a long time, traditional Chinese medicine in clinical practice has been considered to be safe, low toxicity of drugs. In recent decades, with the listing of the many independently developed traditional Chinese medicine injections, compared traditional Chinese medicine, traditional Chinese medicine injections has accurate dose, quick, and other advantages, increasingly widespread clinical application. But in recent years to adverse reactions happened frequently, especially traditional Chinese medicine injection adverse events happened at Honghe Prefecture, Yunnan Province, Datong County, Qinghai Province, Zhongshan City, Guangdong Province in 2008 and 2009.Pharmacovigilance issues of traditional Chinese medicine injection became increasingly serious. Adverse information notification system as established by the State Food and Drug Administration in 2001, making the last decade, the adverse reaction reporting database can be formed. This article is based on the database, because the foreign series of pharmacovigilance data method, preliminary mining of TCM injections pharmacovigilance signal.

Adverse reaction database is broadly divided into epidemiological databases and adverse reactions spontaneous reporting database. Principle, different databases need different pharmacovigilance data mining method, the State Food and Drug Administration’s adverse reaction databases are spontaneous reporting database. The existing signal mining methods are based on the fourfold table; make use of the relative proportions of imbalance in principle to explore the warning signs of adverse reactions. Relative proportions of imbalance also have different angles to measure. This article summarizes the nine existing research point of view, and aims to propose the specific range of these methods, comparative nine kinds of methods of statistical theory and calculation process. As for the method of choice in the practice of pharmacovigilance, this article does not involve.