Pralatrexate Adverse Event Reports from FDA FAERS Database

563 patient reports from the FDA Adverse Event Reporting System (FAERS) spanning Q1 2004 to Q1 2025 were analyzed by Wei Yang in 2026. The dataset contains 2,241 adverse event records for the oncology drug pralatrexate, detailing patient demographics, event types, and outcomes. It was extracted and cleaned from the public FAERS database to study the drug's postmarketing safety profile.

Use Cases

• Detect disproportionate reporting signals like toxic epidermal necrolysis using algorithms (ROR, PRR) on adverse event counts and patient sex subgroups.
• Model the time-to-onset distribution (median 16 days) of adverse events like mucositis using Weibull analysis on reported event dates.
• Identify age-related risk patterns, such as mucosal injury in patients aged ≥65 years versus liver abnormalities in those <65, by cross-tabulating age categories and event types.
• Assess the severity outcomes (death, hospitalization) associated with specific system organ classes like 'General disorders and administration site conditions' (N=354).

Strengths

• Contains 2,241 adverse event reports from 563 patients, providing a focused sample for the drug.
• Covers a 21-year time range (2004-2025) from the FAERS database, allowing longitudinal signal analysis.
• Reports detailed patient demographics: 58.44% male, 45.65% aged ≥65 years.
• Identified 84 positive safety signals using four standard pharmacovigilance algorithms.

Limitations

• Small sample size of only 563 patients, limiting statistical power for rare adverse events.
• Inherent reporting biases of spontaneous FAERS data, such as under-reporting and non-uniform data quality.
• Analysis is confined to a single drug (pralatrexate), restricting generalizability to other therapeutics.

Provenance

Source

FDA Adverse Event Reporting System (FAERS) database.

Collection Method

Standardized data cleaning and extraction of primary suspected drug-related reports, followed by signal detection using ROR, PRR, BCPNN, and MGPS algorithms.

Time Range

First quarter of 2004 through the first quarter of 2025.

Freshness

Data current through Q1 2025, with study published in 2026.

Geography

Primarily United States (FDA database), but may include international reports.