Trends in Reports of Statin-Associated Immune-Mediated Necrotizing Myopathy Using the Japanese Adverse Drug Event Report Database.

IF 1.9 Q3 PHARMACOLOGY & PHARMACY
Akina Takami, Gen Terashima, Takumi Tajima, Koki Yamashita, Ataru Igarashi
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引用次数: 0

Abstract

Background: In October 2016, precautions of the package inserts for ethical drugs containing statins were revised for immune-mediated necrotizing myopathy (IMNM).

Objective: Our objective was to assess the trend in statin-associated IMNM reported before and after the release of the revised precautions in Japan.

Methods: We investigated the number of case reports and estimated annual incidence rate of statin-associated IMNM using the Japanese Adverse Drug Event Report and Japan Medical Data Center (JMDC) databases, respectively. To identify IMNM case reports, we used the preferred term "immune-mediated myositis" (MedDRA version 27.1).

Results: We identified 172 statin-associated IMNMs in 145 case reports of patients between 1 April 2004 and 31 March 2023. The most common suspected statin administered to the patients was rosuvastatin (34.3%), followed by pitavastatin (25.0%) and atorvastatin (22.1%). No statin-associated IMNM was reported in patients who were treated with combination agents containing statins. The number of reported statin-associated IMNMs increased from 3 in 2015 to a peak of 51 in 2019, after which it was 22 (2020), 17 (2021), and 21 (2022) in the following years. The estimated annual incidence rate did not differ with statins, it rarely exceeded 5 per 1,000,000 patients.

Conclusions: There was an increasing trend in the number of statin-associated IMNM after the revised precautions of package inserts for statins were released.

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来源期刊
Drugs - Real World Outcomes
Drugs - Real World Outcomes PHARMACOLOGY & PHARMACY-
CiteScore
3.60
自引率
5.00%
发文量
49
审稿时长
8 weeks
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.
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