Unveiling the Burden of Drug-Induced Impulsivity: A Network Analysis of the FDA Adverse Event Reporting System

Introduction Impulsivity induced by dopaminergic agents, like pramipexole and aripiprazole, can lead to behavioral addictions that impact on social functioning and quality of life of patients and families (e.g., resulting in unemployment, marital problems, anxiety). These secondary effects, interconnected in networks of signs and symptoms, are usually overlooked by clinical trials, not reported in package inserts, and neglected in clinical practice. Objective This study explores the syndromic burden of impulsivity induced by pramipexole and aripiprazole, pinpointing key symptoms for targeted mitigation. Methods An event-event Information Component (IC) on the FDA Adverse Event Reporting System (FAERS) (January 2004 to March 2022) identified the syndrome of events disproportionally co-reported with impulsivity, separately for pramipexole and aripiprazole. A greedy-modularity clustering on composite network analyses (positive pointwise mutual information [PPMI], Ising, Φ ) identified sub-syndromes. Bayesian network modeling highlighted possible precipitating events. Results Suspected drug-induced impulsivity was documented in 7.49% pramipexole and 4.50% aripiprazole recipients. The highest IC concerned obsessive-compulsive disorder (reporting rate = 26.77%; IC median = 3.47, 95% confidence interval [CI] = 3.33–3.57) and emotional distress (21.35%; 3.42, 3.26–3.54) for pramipexole, bankruptcy (10.58%; 4.43, 4.26–4.55) and divorce (7.59%; 4.38, 4.19–4.53) for aripiprazole. The network analysis identified delusional jealousy and dopamine dysregulation sub-syndromes for pramipexole, obesity-hypoventilation and social issues for aripiprazole. The Bayesian network highlighted anxiety and economic problems as potentially precipitating events. Conclusion The under-explored consequences of drug-induced impulsivity significantly burden patients and families. Network analyses, exploring syndromic reactions and potential precipitating events, complement traditional techniques and clinical judgment. Characterizing the secondary impact of reactions will support informed patient-centered decision making.