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Backgrounds:  Proteasome inhibitors (PI) cause toxic peripheral neuropathy (PN), which is one of the dose-limiting adverse events of these treatments. Recent preclinical studies find that factor Xa inhibitor (FXaI), rivaroxaban, promotes PN in animals receiving oxaliplatin. Cancer patients can receive combined therapy of PI and FXaI. This study aimed to identify and characterize the interaction signals for the concomitant use of PI and FXaI resulting in PN.   Methods:  Reports from the United States FDA Adverse Event Reporting System (FAERS) were extracted from the first quarter of 2004 to the first quarter of 2020 for analysis. The Standardized Medical Dictionary for Regulatory Activities (MedDRA) query was used to identify PN cases. We conducted an initial disproportionality investigation to detect PN adverse event signals associated with the combined use of PI and FXaI by estimating a reporting odds ratio (ROR) with a 95% confidence interval (CI). The adjusted RORs were then analyzed by logistic regression analysis (adjusting for age, gender, and reporting year), and additive/multiplicative models were performed to further confirm the findings. Additionally, subset data analysis was performed on the basis of a single drug of PI and FXaI.   Results:  A total of 159,317 adverse event reports (including 2,822 PN reports) were included. The combined use of PI and FXaI was associated with a higher reporting of PN (RORadj = 7.890, 95%CI, 5.321–11.698). The result remained significant based on additive/multiplicative methods. The observed association was consistent in the analysis restricted to all specific PI agents (bortezomib and ixazomib) and FXaI (rivaroxaban), except apixaban.   Conclusion:  Analysis of FAERS data identified reporting associations of PN in the combined use of PI and FXaI, suggesting the need for more robust preclinical and clinical studies to elucidate the relationship.

frontiers in pharmacology

Peripheral Neuropathy During Concomitant Administration of Proteasome Inhibitors and Factor Xa Inhibitors: Identifying the Likelihood of Drug-Drug Interactions