FDA Adverse Event Reports on Drug-Induced Cheilitis with 38 High-Risk Pharmaceuticals

This dataset underpins a pharmacovigilance study analyzing 5,007 cheilitis reports from the FDA Adverse Event Reporting System (2004–2025). It identifies 38 pharmaceuticals significantly associated with the adverse reaction, with disproportionality analysis and molecular docking results. The study includes risk factors like female sex and protective factors like age.

Use Cases

• Identify high-risk pharmaceuticals for cheilitis by analyzing reported odds ratios (ROR), such as the 550.48 signal for crisaborole.
• Model demographic risk factors for adverse events using variables like female sex (OR = 0.771), age, and weight from the logistic regression.
• Validate drug-target interactions for compounds like afatinib and capecitabine using the provided molecular docking binding affinities (ranging from -8.1 to -6.2 kcal/mol).
• Investigate enriched biological pathways like IL-17 and PI3K-Akt signaling linked to core targets IL6, TNF, AKT1, VEGFA, and STAT3.
• Assess drug safety profiles using the ADMET predictions, such as the high liver injury risk for four compounds versus lamotrigine's favorable profile.

Strengths

• Based on 5,007 cheilitis reports from the authoritative FDA Adverse Event Reporting System.
• Integrates population-level pharmacovigilance data with mechanistic validation from 500 ns molecular dynamics simulations.
• Identifies 38 specific pharmaceuticals with significant associations and provides concrete statistical signals (e.g., ROR values).
• Includes multi-method validation through disproportionality analysis, network toxicology, and molecular docking.

Limitations

• The core data is a 107.3 KB DOCX file, which is a manuscript summary, not the raw underlying tabular data; rows and columns are unknown.
• Analysis is confined to U.S. reports, limiting geographic generalizability.
• The dataset's utility for direct machine learning is limited as it presents study results, not feature-rich patient-level records.

Provenance

Source

U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS).

Collection Method

Disproportionality analysis and multivariate logistic regression on reported adverse events, combined with network toxicology and molecular docking.

Time Range

2004–2025

Freshness

Last updated March 2026, with data coverage through 2025.

Geography

United States