2013年至2020年拉脱维亚育龄妇女使用丙戊酸钠风险最小化措施的影响:一项为期7年的全国处方数据库研究。

IF 1.9 Q3 PHARMACOLOGY & PHARMACY Drugs - Real World Outcomes Pub Date : 2023-12-01 Epub Date: 2023-10-12 DOI:10.1007/s40801-023-00394-y
Ieva Rutkovska, Andis Seilis, Zane Neikena, Elita Poplavska
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引用次数: 0

摘要

背景:丙戊酸钠(VPA)在育龄妇女中使用的一个相关安全问题是其致畸性。2014年,欧洲药品管理局(EMA)推出了风险最小化措施(RMM),以减少育龄妇女对VPA的使用,因为对VPA使用的影响没有预期的那么大。2018年,EMA引入了额外的RMM,评估这些干预措施的影响至关重要。目的:本研究的目的是评估2014年和2018年欧洲药品管理局发布的RMM对VPA使用流行率的影响,并描述拉脱维亚癫痫、双相情感障碍和标示外适应症患者使用VPA的流行率和发病比例的趋势。方法:这是一项全国性的基于人群的研究,使用初级保健处方数据库。这项研究包括49岁年龄组的女性和15-49岁接受VPA的男性。本研究评估了VPA使用的患病率和发病率。使用因果影响分析评估了RMM对男性和女性两个研究干预期(2014年第四季度和2018年第四季)的影响。结果:在研究队列中,15-49岁年龄组女性的VPA使用在第一次和第二次干预期后减少,其中在第一次干预期之后,VPA消费流行率的相对降低为-7.7[95%置信区间(CI)-10%,-5.1%],在两个研究期之后为-6.4%(95%CI-11%,-1.5%)。在49岁女孩中,VPA使用增加。在15-49岁的男性中,观察到第一次干预期后有所增加,两次干预期均无显著减少。丙戊酸钠在女孩中的使用率结论:在女孩中发现VPA的使用率在统计学上显著下降
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Impact of Risk Minimisation Measures on Valproate Use among Women of Reproductive Age in Latvia Between 2013 and 2020: A 7-Year Nationwide Prescription Database Study.

Background: A relevant safety concern for the use of valproate (VPA) in women of reproductive age is its teratogenicity. In 2014 European Medicines Agency (EMA) introduced risk minimisation measures (RMMs) to reduce the VPA use by women of reproductive age, where the impact on VPA use was not as large as expected. In 2018, the EMA introduced additional RMMs, and it is essential to assess impact of these interventions.

Objective: The objective of this study was to evaluate the impact of the EMA-published RMMs in 2014 and 2018 on the prevalence of VPA use and to describe trends in the prevalence rate and incidence proportion of VPA use in epilepsy, bipolar disorder and off-label indications in Latvia.

Methods: This was a nationwide population-based study using a primary care prescription database. The study included women in age groups < 15, 15-49 and > 49 years and men in age group 15-49 years who have received VPA. This study assessed the prevalence rate and the incidence proportion of VPA use. The impact of RMMs on the two study intervention periods [fourth quarter (Q4) 2014 and Q4 2018] in men and women was evaluated using causal impact analysis.

Results: In the study cohort, VPA use in women in the age group 15-49 years decreased after the first and second intervention periods, where after the first intervention period the relative reduction in prevalence of VPA consumption was -7.7 [95% confidence interval (CI) -10%, -5.1%] and after both study periods -6.4% (95% CI -11%, -1.5%). In girls < 15 years of age, valproate use decreased after both intervention periods, while in women > 49 years old VPA use increased. In men aged 15-49 years, an increase after the first period and a non-significant decrease after both intervention periods was observed. The prevalence of valproate use in girls < 15 years and women 15-49 years of age with bipolar disorder, epilepsy and off-label indications decreased per 1000 people during the study period. The incidence proportion of VPA use in women aged 15-49 years decreased each year since the beginning of the study period.

Conclusions: A statistically significant decrease in the prevalence of VPA use was identified among girls < 15 years and women 15-49 years of age. In Latvia, an overall good reaction to the EMA RMMs was observed. The effects go beyond the target population and affect the use of VPA in young girls as well.

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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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