# A Comprehensive Analysis of Adverse Events Associated with HER2 Inhibitors Approved for Breast Cancer Using the FDA Adverse Event Report System (FAERS)

## TL;DR

This study analyzed side effects of HER2 inhibitors used in breast cancer treatment using FDA data, revealing distinct patterns that could help improve drug safety and management.

## Contribution

The study provides a comprehensive analysis of adverse event profiles for HER2 inhibitors using FAERS data, revealing distinct patterns by drug class.

## Key findings

- Hair disorders were strongly associated with monoclonal antibodies in HER2 inhibitors.
- PCA revealed distinct adverse event patterns between monoclonal antibodies and tyrosine kinase inhibitors.
- The analysis identified unique adverse event clusters corresponding to different pharmacological classes of HER2 inhibitors.

## Abstract

Background/Objectives: Human epidermal growth factor receptor 2 (HER2) inhibitors have markedly improved outcomes in patients with HER2-positive breast cancer. Clinical treatment often involves the sequential or combined use of multiple HER2 inhibitors, making it essential to clarify their distinct adverse event (AE) profiles. However, AE trends remain insufficiently understood. This study aimed to comprehensively analyze characteristic AEs associated with HER2 inhibitors. Methods: Using the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS, January 2004–September 2024), we conducted disproportionality analyses of AEs associated with HER2 inhibitors approved for breast cancer. Based on the natural logarithm of the reporting odds ratio (lnROR), hierarchical cluster analysis and principal component analysis (PCA) were performed. Results: Disproportionality analysis treating HER2 inhibitors as a single group identified several signals, with hair disorder (ROR 39.93 [95% CI: 37.68–42.32]) as a representative example. Hierarchical clustering showed that monoclonal antibodies (mAbs) and tyrosine kinase inhibitors (TKIs) diverged early in the dendrogram, and clusters broadly corresponded to pharmacological classes. The cluster of hair-related AEs closely corresponded to mAbs. PCA indicated that the first component reflected AE occurrence risk (R2 = 0.655, p < 0.0001), the second component distinguished mAbs from TKIs (tucatinib: r = 0.667; trastuzumab: r = −0.567), and the third component separated molecular targeted agents from antibody–drug conjugates (neratinib: r = 0.521; T-DXd: r = −0.440). Conclusions: FAERS-based analyses enabled visualization of the distinct AE profiles of HER2 inhibitors. These findings may support safe drug selection, risk stratification, and improved AE management strategies.