Disproportionality Analysis of Nusinersen in the Food and Drug Administration Adverse Event Reporting System: A Real-World Postmarketing Pharmacovigilance Assessment

Abstract

Background

Nusinersen is the first drug for precise targeted therapy of spinal muscular atrophy, a rare disease that occurs in one of 10,000 to 20,000 live births. Therefore, thorough and comprehensive reports on the safety of nusinersen in large, real-world populations are necessary. This study aimed to mine the adverse event (AE) signals related to nusinersen through the Food and Drug Administration Adverse Event Reporting System (FAERS) database.

Methods

We extracted reports of AEs with nusinersen as the primary suspect from FAERS between December 2016 and March 2023. Reporting odds ratio (ROR) and Bayesian confidence propagation neural network (BCPNN) were used for AE signal detection.

Results

We extracted a total of 4807 suspected AE cases with nusinersen as the primary suspect from the FAERS database. Among them, 106 positive signals were obtained using the ROR and BCPNN. The highest frequency reported systemic organ class was general disorders and administration site conditions. Common clinical AEs of nusinersen were detected in the FAERS database, such as pneumonia, vomiting, back pain, headache, pyrexia, and post–lumbar puncture syndrome. In addition, we identified potential unexpected serious AEs through disproportionality analysis, including sepsis, seizure, epilepsy, brain injury, cardiorespiratory arrest, and cardiac arrest.

Conclusions

Analyzing large amounts of real-world data from the FAERS database, we identified potential new AEs of nusinersen by disproportionate analysis. It is advantageous for health care professionals and pharmacists to concentrate on effectively managing high-risk AEs of nusinersen, improve medication levels in clinical settings, and uphold patient medication safety.