Review on tree-based scan statistic in drug and vaccine safety monitoring

Abstract

To summarize the development and application of tree-based scan statistic (TreeScan), explain the methodology and provide a reference for future use of this method by reviewing the original pharmacoepidemiological and vaccine studies using the TreeScan. Medline, Embase and Web of Science databases were used for the retrieval of eligible studies using keywords related to TreeScan. A total of 15 eligible studies were included, in which 9 studies explored the adverse events of drugs and 6 studies focused on the safety of vaccines. Three types of models (Poisson probability model, Bernoulli probability model and tree-temporal scan statistic model) of TreeScan were used. The major differences among the three models were 1) whether predefined control was used according to research question, 2) whether the time from exposure to onset of adverse events was considered. Several studies explored its ability by comparing with other methods for adverse event detection or by using known adverse events. This review shows that TreeScan is an effective method for the safety signal detection of drugs or vaccines, which develops rapidly and globally. It is very necessary to promote its use in drug safety monitoring and other related fields in China.