Background: Daratumumab is widely used in multiple myeloma (MM) and light chain amyloidosis (AL amyloidosis). The purpose of this study was to identify adverse event (AE) signals for daratumumab through the FDA Adverse Event Reporting System (FAERS) database to assess its safety in a large sample of people.
Methods: Based on data from the FAERS database, three disproportionality analysis methods were used to mine AE signals for daratumumab, including reporting odd ratio (ROR), proportional reporting ratio (PRR), and bayesian configuration promotion neural network (BCPNN).
Results: A total of 9220 AE reports with daratumumab as the primary suspect drug were collected, containing 23,946 AEs. Within these reports, 252 preferred terms (PT) levels, 73 high level term (HLT) levels and 11 system organ class (SOC) levels of AE signals were detected, along with some new AEs. Most AEs occurred within the first month after drug administration.
Conclusion: Our findings were consistent with the results of established studies that daratumumab has a good safety profile. The newly identified AEs are of concern and prospective clinical studies are needed to confirm whether they are causally related to daratumumab. This study provided an early warning for the safe use of daratumumab and also provided guidance for further safety studies.
Keywords: FAERS; Pharmacovigilance; adverse events; daratumumab; data mining; disproportionality analysis.