The Association Between Deep Vein Thrombosis, Pulmonary Embolism, and Janus Kinase Inhibitors: Reporting Status and Signal Detection in the Japanese Adverse Drug Event Report Database.
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Abstract
Background: Although Janus kinase (JAK) inhibitors have expanding indications, deep vein thrombosis (DVT) and pulmonary embolism (PE) are serious adverse events associated with their use. Moreover, their analysis using the Japanese database of spontaneous adverse drug reaction reports has not yet been conducted.
Objective: The objective of this study was to analyze the Japanese Adverse Drug Event Report database (JADER) to evaluate the association between JAK inhibitors and DVT and PE.
Methods: JADER reports from April 2004 to October 2023 were analyzed. A classification of reports for the period covered was performed by drug, and an imbalance analysis was performed with oral JAK inhibitors as the target drug and DVT, PE, and "embolic and thrombotic events, venous" (Standardised MedDRA Query; SMQ) as the target adverse events. Reported odds ratios (ROR) and information components (IC) were calculated for signal detection.
Results: Overall, 6631 JAK inhibitor-related adverse events were reported, including 60 and 41 cases of DVT and PE, respectively. The ROR and IC of the JAK inhibitors for DVT were 2.52 (1.95-3.25) and 1.27 (0.41-2.13), while those of baricitinib for DVT were 4.37 (2.83-6.73) and 1.90 (0.47-3.33), respectively. ROR signals were detected for JAK inhibitors for PE and "embolic and thrombotic events, venous (SMQ)," overall and for several JAK inhibitors but none for IC.
Conclusions: Several JAK inhibitors are under postmarketing phase vigilance, and the number of reported adverse events is low. However, when administering these drugs, care should be taken to avoid the development of thromboembolism, considering the patient's background.
期刊介绍:
Drugs - Real World Outcomes targets original research and definitive reviews regarding the use of real-world data to evaluate health outcomes and inform healthcare decision-making on drugs, devices and other interventions in clinical practice. The journal includes, but is not limited to, the following research areas: Using registries/databases/health records and other non-selected observational datasets to investigate: drug use and treatment outcomes prescription patterns drug safety signals adherence to treatment guidelines benefit : risk profiles comparative effectiveness economic analyses including cost-of-illness Data-driven research methodologies, including the capture, curation, search, sharing, analysis and interpretation of ‘big data’ Techniques and approaches to optimise real-world modelling.