Signal mining and safety profile analysis of lapatinib: a pharmacovigilance analysis of the FDA Adverse Event Reporting System (FAERS) database.

ABSTRACT:

Background

There remains a gap in understanding lapatinib's real-world safety, particularly in rare adverse events (AEs). Thus, this study aims to evaluate lapatinib's safety by (1) performing data mining of the FDA Adverse Event Reporting System (FAERS); and (2) detecting and analysing safety signals associated with lapatinib that may require monitoring.

Methods

FAERS data from March 2007 to July 2024 were analysed via OpenVigil (version 2.1). AEs were categorised into preferred terms (PTs) and system organ classes (SOCs) using the Medical Dictionary for Regulatory Activities. We used descriptive analysis to analyse report characteristics and four signal detection algorithms to quantify risk signals, including Proportional Reporting Ratio (PRR), Reporting Odds Ratio (ROR),

SUBMITTER: Cerbito E 

PROVIDER: S-EPMC12802520 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature