Utilizing temporal pattern of adverse event reports to identify potential late-onset adverse events

ABSTRACT

Objectives

Through the use of FDA adverse event reporting system (FAERS) dataset, this study analyzes the pattern of time-to-event (TTE) for drugs and adverse events, and suggest ways to identify candidate late-onset events for monitoring.

Methods

The duration between administration date of the drug and the onset of adverse events was explored with using FAERS data from 2012–2021. The fold change of proportional reporting ratios or reporting odds ratios were calculated to identify enriched events in the later period and to suggest the late-onset events for further monitoring. To compare the findings, we used the claims database of the Korean National Health Insurance Service (NHIS).

Results

A total of 1,426,781 reports were included. The median TTE was 10 days (interquartile range [IQR]: 0–98 days), with 11.5% (n = 164,093) reporting events that occurred at least one year after administration. TTE and fold change analysis captured historical cases of late-onset events, while generating an additional less-explored list of events. The results for tumor necrosis factor (TNF) inhibitors were compared using the NHIS dataset.

Conclusion

Our study provides a comprehensive analysis of the FAERS dataset, focusing on TTE data. Periodic summarization of reports would be helpful in monitoring the late-onset events.

KEYWORDS:

• Drug-related side effects and adverse reactions
• Pharmacoepidemiology
• Pharmacovigilance
• administrative claims, healthcare
• late onset disorders

Declaration of interests

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Author contribution statement

JHK wrote the manuscript; JHK and YKS designed the study; JHK and YKS analyzed the results; and all authors edited and approved the manuscript.

Data availability statement

The FDA Adverse Event dataset can be accessed through the FDA Adverse Event Reporting System. The processed FDA Adverse Event dataset used for our analysis is available at the following repository: https://github.com/kimkimjh/temp-FAERS. The National Health Insurance Service dataset is not accessible due to concerns regarding patient privacy.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/14740338.2024.2309223

Additional information

Funding

This paper was funded by the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education (grant number: NRF-2021R1F1A1060827, NRF-2022R1C1C1011730). This paper was supported by research funds for newly appointed professors of Jeonbuk National University in 2021.