A real-world pharmacovigilance study of FDA adverse event reporting system events for atogepant

ABSTRACT

Background

Atogepant, an orally administered, small-molecule, calcitonin gene-related peptide (CGRP) receptor antagonist, is being investigated for the treatment of migraine.

Methods

We collected data from the US Food and Drug Administration Adverse Event Reporting System (FAERS) database. Four algorithms (ROR, PRR, BCPNN, and EBGM) were used as measures to detect signals of atogepant-associated adverse events (AEs) in real-world data.

Result

Of the 3,552,072 reports, 2876 expressly stated the use of atogepant. Women accounted for the majority of adverse events (AEs), with a notable age concentration of 45–65 years. The percentage of reported adverse events was the highest in the United States. Significant system organ categories (SOC) included nervous system disorders, gastrointestinal disorders, nervous system disorders, surgical and medical procedures, ear and labyrinth disorders. Notably, preferred terms (PTs) related to atogepant include migraine, constipation, nausea, vertigo, somnolence, decreased appetite, dizziness and fatigue. Unexpected adverse events such as abnormal dreams, self-injurious ideation, brain fog, tension headache, nightmare, brain neoplasm, feeling abnormal, euphoric mood, hyperacusis and post concussion syndrome were also identified.

Conclusions

The present investigation has detected new and unexpected signals of atogepant-related adverse drug reactions (ADRs). In order to confirm these solve safety issues that were previously overlooked, more research is necessary.

KEYWORDS:

• Adverse event
• data mining
• FAERS
• pharmacovigilance
• atogepant

Declaration of interest

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

One reviewer has been employed by Lundbeck for the past 2 years. The remaining reviewers have no other relevant financial relationships or otherwise to disclose.

Author contribution statement

Conceptualization: Feichi Chen.

Data curation: Feichi Chen and Heli Wen.

Data analysis: Feichi Chen, Heli Wen and Yitian Ding.

Writing – original draft: Feichi Chen, Heli Wen and Yitian Ding.

Supervision, writing – review and editing: Feichi Chen.

Additional information

Funding

This paper was not funded.