FDA Adverse Event Reports on Drug-Induced Cheilitis with 38 Associated Drugs

The dataset underpins a pharmacovigilance study analyzing 5,007 cheilitis reports from the U.S. FDA Adverse Event Reporting System (2004–2025). It identifies 38 pharmaceuticals significantly associated with the condition, with disproportionality analysis (ROR) and molecular docking results for key drug-target interactions.

Use Cases

• Identify high-risk drugs for cheilitis by analyzing disproportionality signals like ROR values, such as the 550.48 signal for crisaborole.
• Investigate demographic risk factors for drug-induced cheilitis using multivariate logistic regression results, including the female sex as an independent risk factor (OR = 0.771).
• Validate binding interactions between high-risk drugs like afatinib and core molecular targets such as EGFR using molecular docking affinity scores (e.g., -8.1 kcal/mol).
• Explore enriched biological pathways (e.g., IL-17, TNF, PI3K-Akt) linked to cheilitis through network toxicology analysis of central targets like IL6 and TNF.
• Assess predicted drug safety profiles, such as the high risk of drug-induced liver injury for four compounds versus the favorable profile of lamotrigine from ADMET analysis.

Strengths

• Analysis is based on 5,007 individual cheilitis adverse event reports from the FDA.
• Identifies 38 specific pharmaceuticals with significant statistical associations to the condition.
• Integrates multiple methodologies: disproportionality analysis, network toxicology, and molecular docking with 500 ns dynamics simulations.
• Provides concrete statistical measures like ROR values (e.g., 42.61 for isotretinoin) and molecular binding affinities (e.g., -8.1 kcal/mol).

Limitations

• The core data is a 65.2 KB DOCX file, which is a textual summary of the study rather than the raw, analyzable tabular data.
• The underlying rows, columns, and sample data for the 5,007 reports are unavailable, limiting direct computational analysis.
• The dataset's scope is limited to cheilitis reports from a single reporting system (FAERS) in the United States.

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, supplemented by network toxicology and molecular docking simulations.

Time Range

2004–2025

Freshness

Data covers reports from 2004 to 2025; the study was last updated in March 2026.

Geography

United States