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历史帕金森病试验的纵向荟萃分析,为未来试验设计提供信息。

Longitudinal Meta-Analysis of Historical Parkinson's Disease Trials to Inform Future Trial Design.

机构信息

Clinical Pharmacology Modeling and Simulation, GSK, Upper Providence, Pennsylvania, USA.

出版信息

Mov Disord. 2023 Sep;38(9):1716-1727. doi: 10.1002/mds.29514. Epub 2023 Jul 3.


DOI:10.1002/mds.29514
PMID:37400277
Abstract

BACKGROUND: The outcome of clinical trials in neurodegeneration can be highly uncertain due to the presence of a strong placebo effect. OBJECTIVES: To develop a longitudinal model that can enhance the success of future Parkinson's disease trials by quantifying trial-to-trial variations in placebo and active treatment response. METHODS: A longitudinal model-based meta-analysis was conducted on the total score of Unified Parkinson's Disease Rating Scale (UPDRS) Parts 1, 2, and 3. The analysis included aggregate data from 66 arms (observational [4], placebo [28], or investigational-drug-treated [34]) from 4 observational studies and 17 interventional trials. Inter-study variabilities in key parameters were estimated. Residual variability was weighted by the size of study arms. RESULTS: The baseline total UPDRS was estimated to average at 24.5 points. Disease score was estimated to worsen by 3.90 points/year for the duration of the treatments; whilst notably, arms with a lower baseline progressed faster. The model captured the transient nature of the placebo response and sustained symptomatic drug effect. Both placebo and drug effects peaked within 2 months; although, 1 year was needed to observe the full treatment difference. Across these studies, the progression rate varied by 59.4%, the half-life for offset of placebo response varied by 79.4%, and the amplitude for drug effect varied by 105.3%. CONCLUSION: The longitudinal model-based meta-analysis describes UPDRS progression rate, captures the dynamics of the placebo response, quantifies the effect size of the available therapies, and sets the expectation of uncertainty for future trials. The findings provide informative priors to enhance the rigor and success of future trials of promising agents, including potential disease modifiers. © 2023 GSK. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

摘要

背景:由于存在强烈的安慰剂效应,神经退行性疾病临床试验的结果可能高度不确定。

目的:通过量化试验中安慰剂和活性治疗反应的变异性,开发一种纵向模型,从而提高未来帕金森病试验的成功率。

方法:对统一帕金森病评定量表(UPDRS)第 1、2 和 3 部分的总分进行基于纵向模型的荟萃分析。该分析包括来自 4 项观察性研究和 17 项干预性试验的 66 个臂(观察[4]、安慰剂[28]或研究药物治疗[34])的汇总数据。估计了关键参数的研究间变异性。研究臂的大小对残余变异性进行加权。

结果:基线总 UPDRS 估计平均为 24.5 分。疾病评分估计在治疗期间每年恶化 3.90 分;值得注意的是,基线较低的臂进展更快。该模型捕捉到了安慰剂反应的短暂性和持续的症状性药物效应。安慰剂和药物效应均在 2 个月内达到峰值;尽管需要 1 年才能观察到完全的治疗差异。在这些研究中,进展速度变化 59.4%,安慰剂反应消退的半衰期变化 79.4%,药物效应的幅度变化 105.3%。

结论:基于纵向模型的荟萃分析描述了 UPDRS 进展速度,捕捉了安慰剂反应的动态,量化了现有疗法的效应大小,并为未来试验设定了不确定性的预期。这些发现为提高有前途的药物的未来试验的严谨性和成功率提供了有价值的先验信息,包括潜在的疾病修饰剂。© 2023 GSK。运动障碍由 Wiley Periodicals LLC 代表国际帕金森病和运动障碍学会出版。

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