Signal mining and analysis of trifluridine/tipiracil adverse events based on real-world data from the FAERS database.

Abstract

The objective of this research is to scrutinize adverse events (AEs) linked to Trifluridine/Tipiracil (TFTD/TPI), using data from the FDA Adverse Event Reporting System (FAERS) database. The AEs data related to TFTD/TPI were collected from the fourth quarter of 2015 through the fourth quarter of 2023. After normalizing the data, multiple signal quantification techniques including Proportional Reporting Ratio (PRR), Reporting Odds Ratio (ROR), Bayesian approaches such as Bayesian Confidence Propagation Neural Network (BCPNN) and the Multi-item Gamma Poisson Shrinker (MGPS) were used for overall and subgroup analysis and visualization analyses were performed. From the FAERS database, we analyzed 13,520,073 reports, identifying 8,331 as primary suspect (PS) AEs for TFTD/TPI, occurring across 27 organ systems. The study retained 99 significant disproportionality Preferred Terms (PTs) across four algorithms and unveiled unexpected serious AEs such as iron deficiency and intestinal perforation, hepatic failure, cholangitis and so on. The median onset of TFTD/TPI-associated AEs was 44days (IQR 20-97 days), with most occurring within the first 30 days of treatment. This research uncovers critical new safety signals for TFTD/TPI, supporting its clinical monitoring and risk identification.