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用于评估阿尔茨海默病中生物标志物与临床终点之间关系的统计框架。

A Statistical Framework for Assessing the Relationship between Biomarkers and Clinical Endpoints in Alzheimer's Disease.

机构信息

Tianle Chen, Biogen Inc., 225 Binney St., Cambridge, MA 02142, Email address:

出版信息

J Prev Alzheimers Dis. 2024;11(5):1228-1240. doi: 10.14283/jpad.2024.126.

DOI:10.14283/jpad.2024.126
PMID:39350368
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11436399/
Abstract

Changes in biomarker levels of Alzheimer's disease (AD) reflect underlying pathophysiological changes in the brain and can provide evidence of direct and downstream treatment effects linked to disease modification. Recent results from clinical trials of anti-amyloid β (Aβ) treatments have raised the question of how to best characterize the relationship between AD biomarkers and clinical endpoints. Consensus methodology for assessing such relationships is lacking, leading to inconsistent evaluation and reporting. In this review, we provide a statistical framework for reporting treatment effects on early and late accelerating AD biomarkers and assessing their relationship with clinical endpoints at the subject and group levels. Amyloid positron emission tomography (PET), plasma p-tau, and tau PET follow specific trajectories during AD and are used as exemplar cases to contrast biomarkers with early and late progression. Subject-level correlation was assessed using change from baseline in biomarkers versus change from baseline in clinical endpoints, and interpretation of the correlation is dependent on the biomarker and disease stage. Group-level correlation was assessed using the placebo-adjusted treatment effects on biomarkers versus those on clinical endpoints in each trial. This correlation leverages the fundamental advantages of randomized placebo-controlled trials and assesses the predictivity of a treatment effect on a biomarker or clinical benefit. Harmonization in the assessment of treatment effects on biomarkers and their relationship to clinical endpoints will provide a wealth of comparable data across clinical trials and may yield new insights for the treatment of AD.

摘要

阿尔茨海默病(AD)生物标志物水平的变化反映了大脑中潜在的病理生理变化,并能提供与疾病修饰相关的直接和下游治疗效果的证据。最近抗淀粉样蛋白β(Aβ)治疗临床试验的结果提出了一个问题,即如何最好地描述 AD 生物标志物与临床终点之间的关系。缺乏评估这种关系的共识方法,导致评估和报告不一致。在这篇综述中,我们提供了一个报告早期和晚期加速 AD 生物标志物治疗效果的统计框架,并评估了它们在个体和群体水平上与临床终点的关系。正电子发射断层扫描(PET)淀粉样蛋白、血浆 p-tau 和 tau PET 在 AD 期间遵循特定的轨迹,被用作对比具有早期和晚期进展的生物标志物的示例。使用生物标志物与临床终点从基线的变化来评估个体水平的相关性,并且相关性的解释取决于生物标志物和疾病阶段。使用每个试验中安慰剂调整后的生物标志物与临床终点的治疗效果来评估群体水平的相关性。这种相关性利用了随机安慰剂对照试验的基本优势,并评估了治疗效果对生物标志物或临床获益的预测性。对生物标志物治疗效果及其与临床终点关系的评估的协调将为临床试验提供大量可比数据,并可能为 AD 的治疗提供新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3a5/11436399/e0adfa6dc0dc/42414_2024_126_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3a5/11436399/87dc139f9440/42414_2024_126_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3a5/11436399/02cccd18c1de/42414_2024_126_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3a5/11436399/2dcfee6a1a89/42414_2024_126_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3a5/11436399/e0adfa6dc0dc/42414_2024_126_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3a5/11436399/87dc139f9440/42414_2024_126_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3a5/11436399/02cccd18c1de/42414_2024_126_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3a5/11436399/2dcfee6a1a89/42414_2024_126_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3a5/11436399/e0adfa6dc0dc/42414_2024_126_Fig4_HTML.jpg

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