Outcomes and Factors Associated with Insufficient Effectiveness of Acute Treatments of Migraine in Japan: Results of the ObserVational survey of the Epidemiology, tReatment, and Care Of MigrainE (OVERCOME [Japan]) Study.

IF 1.9 Q3 PHARMACOLOGY & PHARMACY Drugs - Real World Outcomes Pub Date : 2023-09-01 Epub Date: 2023-06-06 DOI:10.1007/s40801-023-00368-0
Koichi Hirata, Mika Komori, Kaname Ueda, Anthony J Zagar, Yongin Kim, Dena H Jaffe, Yasuhiko Matsumori, Takao Takeshima
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Abstract

Background: Knowledge of patient outcomes and treatment effectiveness associated with acute migraine treatments in Japan is lacking.

Objective: To describe patient-reported outcomes (PROs) and treatment effectiveness in three acute treatment groups from OVERCOME (Japan): over-the-counter (OTC) only, prescription nonsteroidal anti-inflammatory drugs/acetaminophen (Rx-NSAIDs/ACE) only, and triptans.

Methods: OVERCOME (Japan) was an observational, cross-sectional, population-based web survey of people with migraine (July-September 2020). PROs, including the Migraine-Specific Quality of Life Questionnaire (MSQ), Migraine Interictal Burden Scale (MIBS-4), Migraine Disability Assessment (MIDAS), and Work Productivity and Activity Impairment Questionnaire: Migraine (WPAI-M), were compared pairwise between treatment groups. Logistic regression was used to examine treatment effectiveness.

Results: The analysis included 9075 survey respondents (OTC only: n = 5791; Rx-NSAIDs/ACE only: n = 751; triptans: n = 2533). Triptan users reported the lowest MSQ scores, most severe disability (MIDAS: 20.7% versus 6.3% and 11.6%) and severe interictal burden (MIBS-4: 50.1% versus 21.2% and 19.8%), and greatest work impairment (WPAI-M: 50.4% versus 32.2% and 30.8%) compared with the OTC and Rx-NSAIDs/ACE groups, respectively. Treatment effectiveness was very poor-to-poor for 60.9%, 43.1%, and 47.6% of the triptan, OTC, and Rx-NSAIDs/ACE groups, respectively. Severe interictal burden was significantly associated with insufficient treatment effectiveness (odds ratios, severe versus no burden: 0.47 [95% confidence interval: 0.40-0.54], 0.56 [0.35-0.89], and 0.41 [0.32-0.52], for the OTC, Rx-NSAIDs/ACE, and triptan groups, respectively).

Conclusion: People with high migraine burden used triptans for acute treatment, but many reported poor treatment effectiveness. Education may be required to promote better treatments, including earlier introduction of migraine-specific acute and preventive medications.

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日本偏头痛急性治疗效果不佳的结果和相关因素:偏头痛流行病学、治疗和护理的观察性调查结果[日本]。
背景:对日本急性偏头痛治疗的患者结局和治疗效果缺乏了解。目的:描述OVERCOME(日本)三个急性治疗组的患者报告结果(PROs)和治疗效果:仅非处方药(OTC)、仅处方非甾体抗炎药/对乙酰氨基酚(Rx-NSAIDs/ACE)和曲坦。方法:OVERCOME(日本)是一项针对偏头痛患者的观察性、横断面、基于人群的网络调查(2020年7月至9月)。PROs,包括偏头痛特异性生活质量问卷(MSQ)、偏头痛发作间负担量表(MIBS-4)、偏头痛残疾评估(MIDAS)和工作效率和活动障碍问卷:偏头痛(WPAI-M),在治疗组之间进行配对比较。采用Logistic回归检验治疗效果。结果:该分析包括9075名调查对象(仅OTC:n=5791;仅Rx-NSAIDs/ACE:n=751;曲坦:n=2533)。与OTC和Rx NSAIDs/ACE组相比,Triptan用户报告的MSQ得分最低,残疾最严重(MIDAS:20.7%对6.3%和11.6%),发作间负担严重(MIBS-4:50.1%对21.2%和19.8%),工作障碍最大(WPAI-M:50.4%对32.2%和30.8%)。曲坦组、OTC组和Rx-NSAIDs/ACE组的治疗效果分别为60.9%、43.1%和47.6%。严重的发作间期负荷与治疗效果不足显著相关(OTC、Rx-NSAIDs/ACE和曲坦组的比值比,严重负荷与无负荷比值比分别为0.47[95%置信区间:0.40-0.54]、0.56[0.35-0.89]和0.41[0.32-0.52]),但许多人报告治疗效果不佳。可能需要进行教育以促进更好的治疗,包括尽早引入针对偏头痛的急性和预防药物。
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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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