Treatment Patterns in Patients with Incident Parkinson's Disease in the United States

美国新发帕金森病患者的治疗模式

阅读:1

Abstract

BACKGROUND: Treatment patterns in Parkinson's disease (PD) have not been extensively studied for nearly two decades. Insurance claims are appropriate for such analysis. OBJECTIVE: To understand the standard of care use of symptomatic treatments in new cases of PD and factors associated with treatment choice. METHODS: Retrospective cohort study using claims data from the United States between 2008 and 2016. We used Kaplan-Meier methodology to estimate time to treatment start and switch or add-on therapy and Cox proportional hazards models to identify predictors. RESULTS: We identified 68,532 patients eligible for treatment pattern analyses. Median time from diagnosis until first treatment was 37 days (95% confidence interval: 36-38). Two distinct patterns of treatment initiation were identified: fast initiators and patients with delayed treatment start (or no recorded treatment). Levodopa therapies were the most commonly prescribed treatment class (52.6%). Increased age was associated with shorter time to start of treatment with levodopa. Younger age was associated with shorter time to initiation of dopamine agonists and other symptomatic treatments. Patients that initiated treatment with levodopa/combinations had the fewest switches/add-ons [30.4%; median time 7.29 (6.71, 8.13) years]. Older patients had fewer switch/add-on therapies, but only in the group that started with levodopa/combination therapy. CONCLUSIONS: Time from diagnosis to treatment start was relatively short, suggesting that PD diagnosis, as reflected in the database, is closely linked to start of symptomatic treatment. Levodopa treatment remains the most common treatment, especially for older patients. Delayed treatment start was associated with increased age and comorbidity.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。