Effect of database profile variation on drug safety assessment: an analysis of spontaneous adverse event reports of Japanese cases

Abstract

BackgroundThe use of a statistical approach to analyze cumulative adverse event (AE) reports has been encouraged by regulatory authorities. However, data variations affect statistical analyses (eg, signal detection). Further, differences in regulations, social issues, and health care systems can cause variations in AE data. The present study examined similarities and differences between two publicly available databases, ie, the Japanese Adverse Drug Event Report (JADER) database and the US Food and Drug Administration Adverse Event Reporting System (FAERS), and how they affect signal detection.MethodsTwo AE data sources from 2010 were examined, ie, JADER cases (JP) and Japanese cases extracted from the FAERS (FAERS-JP). Three methods for signals of disproportionate reporting, ie, the reporting odds ratio, Bayesian confidence propagation neural network, and Gamma Poisson Shrinker (GPS), were used on drug-event combinations for three substances frequently recorded in both systems.ResultsThe two databases showed similar elements of AE reports, but no option was provided for a shareable case identifier. The average number of AEs per case was 1.6±1.3 (maximum 37) in the JP and 3.3±3.5 (maximum 62) in the FAERS-JP. Between 5% and 57% of all AEs were signaled by three quantitative methods for etanercept, infliximab, and paroxetine. Signals identified by GPS for the JP and FAERS-JP, as referenced by Japanese labeling, showed higher positive sensitivity than was expected.ConclusionThe FAERS-JP was different from the JADER. Signals derived from both datasets identified different results, but shared certain signals. Discrepancies in type of AEs, drugs reported, and average number of AEs per case were potential contributing factors. This study will help those concerned with pharmacovigilance better understand the use and pitfalls of using spontaneous AE data.

Evaluation of pregabalin-induced adverse events related to falls using the FDA adverse event reporting system and Japanese Adverse Drug Event Report databases

“…The comparison study demonstrated distinct discrepancies in reported drugs, reported AEs, seriousness and average number of reported events per case, between the JADER and FAERS . Since differences can arise as a result of discrepancies in reporting rules and customs in each country such as reporters and reported AE terms, which are associated with regulations, the two databases showed different features . For example, SRS databases mostly depend on the compliance of pharmaceutical companies to report according to regulatory requirements.…”

“…For example, SRS databases mostly depend on the compliance of pharmaceutical companies to report according to regulatory requirements. US companies need to submit case reports of non‐serious AEs, but reporting of known non‐serious AEs is not mandatory for Japanese companies . Each company has its own operational rules for AE reports, which makes them impossible for researchers to validate the contents of SRS databases .…”

Evaluation of Drug-Induced Photosensitivity Using the Japanese Adverse Drug Event Report (JADER) Database

“…Nomura et al reported that there are differences in the reported numbers of AEs between the JADER and FAERS; however, the number of shared reports between JADER and FAERS is unknown. 22) Regional differences in drug prescriptions or genetic backgrounds might be responsible for the differences in AEs. 22) The number of reports published in the JADER database is larger than that recorded in the FAERS database.…”

“…22) Regional differences in drug prescriptions or genetic backgrounds might be responsible for the differences in AEs. 22) The number of reports published in the JADER database is larger than that recorded in the FAERS database. Therefore, we evaluated the seasonal variation of DIP using a logistic regression model.…”

Prodromal signs and symptoms of serious infections with tocilizumab treatment for rheumatoid arthritis: Text mining of the Japanese postmarketing adverse event-reporting database

“…Post-marketing AE-reporting databases are among the fundamental resources in pharmacovigilance [11]. Previous reports, including some in patients treated with TCZ, have focused on structured data elements, such as age, sex, and onset of disease [7,12,13].…”