Department of Clinical Neurosciences, Villa San Benedetto Menni Hospital, Hermanas Hospitalarias , Albese Con Cassano (Como), Italy.
Department of Biomedical Sciences, Humanitas University , Pieve Emanuele (Milan), Italy.
Expert Opin Pharmacother. 2020 Oct;21(14):1699-1711. doi: 10.1080/14656566.2020.1779220. Epub 2020 Jun 16.
A substantial number of patients with PD experience relapse after the discontinuation of effective pharmacotherapy, leading to detrimental effects on the individuals and considerable societal costs. This suggests the need to optimize pharmacotherapy to minimize relapse risk. The present systematic review examines randomized, double-blind, placebo-controlled relapse prevention studies published over the last 20 years involving recommended medications. The authors aim to provide an overview of this topic and evaluate whether recent advances were achieved. Only seven studies were included, providing limited results. One-year maintenance pharmacotherapy with constant doses had protective effects against relapse in patients who had previously exhibited satisfactory responses to the same medication at the same doses. The duration of maintenance treatment did not influence relapse risk. No data were available concerning the use of lower doses or the predictors of relapse. Relapse prevention in PD has received limited attention. Recent progress and conclusive indications are lacking. Rethinking pharmacological research in PD may be productive. Collecting a wide range of clinical and individual features/biomarkers in large-scale, multicenter long-term naturalistic studies, and implementing recent technological innovations (e.g., electronic medical records/'big data' platforms, wearable devices, and machine learning techniques) may help identify reliable predictive models.
相当数量的 PD 患者在有效药物治疗停止后会经历复发,这对个人和社会造成了不利影响和巨大的经济负担。这表明需要优化药物治疗以最小化复发风险。本系统评价回顾了过去 20 年发表的涉及推荐药物的随机、双盲、安慰剂对照复发预防研究。作者旨在提供该主题的概述并评估是否取得了近期进展。只有 7 项研究被纳入,结果有限。对于先前对相同药物和相同剂量表现出满意反应的患者,用固定剂量进行为期一年的维持药物治疗对预防复发有保护作用。维持治疗的持续时间并不影响复发风险。关于使用较低剂量或复发预测因素的数据尚不可用。PD 的复发预防受到的关注有限。缺乏近期进展和明确的适应证。重新思考 PD 的药物研究可能会富有成效。在大型、多中心的长期自然史研究中收集广泛的临床和个体特征/生物标志物,并应用最新的技术创新(例如电子病历/“大数据”平台、可穿戴设备和机器学习技术),可能有助于识别可靠的预测模型。