2．A Checklist of Important Points in Research Using JADER
- VernacularTitle:2．JADER を用いた研究発表の際に留意すべきチェックリストの提案
- Author:
Takamasa SAKAI
1
Author Information
- Keywords: spontaneous reporting; signal detection; data mining; checklist
- From:Japanese Journal of Pharmacoepidemiology 2020;25(2):64-73
- CountryJapan
- Language:Japanese
- Abstract: Spontaneous reporting is an important source of information in pharmacovigilance. In Japan, the Japanese Adverse Drug Event Report database (JADER) was released in 2012, and this has led to numerous conference presentations and academic research papers that have reported the detection of signals based on the use of data mining methods. However, spontaneous reporting generally has certain limitations, including under-reporting, a lack of denominator information, and the effects of reporting bias, and these problems apply equally to JADER. The system of collecting spontaneous reports also influences the results obtained based on JADER analysis, as JADER in principle comprises serious adverse drug event reports and includes solicited reports. The detection of signals showing statistical significance does not necessarily imply a causal relationship between a particular drug and adverse events, and consequently, the cause of the signals detected requires careful interpretation. However, it has been pointed out that findings are sometimes accepted without considering the limitations.For pharmaceutical companies, the Guidance on good pharmacovigilance practices Module Ⅸ and Guidance for Industry - Good Pharmacovigilance Practices and Pharmacoepidemiologic Assessment are available in the European Union and United States, respectively, for the purpose of signal management in pharmacovigilance activities. In contrast, there are limited resources to which researchers can refer when they publish scientific findings obtained using spontaneous reporting databases. To rectify this deficiency, we created a “checklist of important points to be noted during research that uses the data mining method in JADER (mainly signal detection by disproportionality analysis)” for the benefit of researchers using JADER. That study was supported by a Grant for Research Projects of the Japanese Society of Drug Informatics in 2017. In this article, we provide an overview of the checklist, with reference to the “Report of CIOMS Working Group Ⅷ： practical aspects of signal detection in pharmacovigilance,” which was used as a source when creating the checklist.
