Comparative pharmacovigilance of Levodopa and Pramipexole: a disproportionality analysis of the FAERS database

This study aimed to comprehensively characterize and compare the safety profiles of Levodopa and Pramipexole, two cornerstone therapies for Parkinson's disease (PD), using real-world data from the FDA Adverse Event Reporting System (FAERS).

A disproportionality analysis was conducted on FAERS data from Q1 2004 to Q2 2025. Reports listing Levodopa or Pramipexole as the 'primary suspect' drug were extracted and deduplicated. Four established algorithms (ROR, PRR, BCPNN, and EBGM) were employed for signal detection at both the System Organ Class (SOC) and Preferred Term (PT) levels. A sensitivity analysis excluding restless legs syndrome (RLS)-indicated Pramipexole reports was performed to assess indication bias.

The analysis included 5,410 Levodopa and 6,894 Pramipexole reports. Distinct demographic and reporting patterns were observed. At the SOC level, Levodopa's strongest signal was in "Respiratory, thoracic and mediastinal disorders" (EBGM05 = 4.46), while Pramipexole's was in "Psychiatric disorders" (EBGM05 = 5.85). At the PT level, Levodopa was strongly associated with "Saliva discolouration" (EBGM05 = 769.94) and previously unhighlighted events like "Choking sensation" (EBGM05 = 71.68). Pramipexole showed extreme signals for "Restless legs augmentation syndrome" (EBGM05 = 1092.07) and "Gambling disorder" (EBGM05 = 610.24). A high frequency (31.47%) of Levodopa-associated events occurred within the first 30 days of treatment. The sensitivity analysis confirmed that Pramipexole's neuropsychiatric signals remained robust after excluding RLS-indicated reports.

This large-scale study confirms the well-established risks of both drugs and identifies potential new safety signals for Levodopa, particularly concerning respiratory manifestations. The fundamentally distinct risk profiles underscore the necessity for drug-specific monitoring strategies and caution in combination therapy. These findings provide critical real-world evidence for optimizing risk-benefit management in PD.