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利用历史数据促进阿尔茨海默病的临床预防试验?对纵向 MCI(轻度认知障碍)数据集的分析。

Using historical data to facilitate clinical prevention trials in Alzheimer disease? An analysis of longitudinal MCI (mild cognitive impairment) data sets.

机构信息

University of Applied Sciences Koblenz, Koblenz, Germany.

University Department of Geriatric Medicine FELIX PLATTER, Basel, Switzerland.

出版信息

Alzheimers Res Ther. 2021 May 7;13(1):97. doi: 10.1186/s13195-021-00832-5.

Abstract

BACKGROUND

The Placebo Group Simulation Approach (PGSA) aims at partially replacing randomized placebo-controlled trials (RPCTs), making use of data from historical control groups in order to decrease the needed number of study participants exposed to lengthy placebo treatment. PGSA algorithms to create virtual control groups were originally derived from mild cognitive impairment (MCI) data of the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. To produce more generalizable algorithms, we aimed to compile five different MCI databases in a heuristic manner to create a "standard control algorithm" for use in future clinical trials.

METHODS

We compared data from two North American cohort studies (n=395 and 4328, respectively), one company-sponsored international clinical drug trial (n=831) and two convenience patient samples, one from Germany (n=726), and one from Switzerland (n=1558).

RESULTS

Despite differences between the five MCI samples regarding inclusion and exclusion criteria, their baseline demographic and cognitive performance data varied less than expected. However, the five samples differed markedly with regard to their subsequent cognitive performance and clinical development: (1) MCI patients from the drug trial did not deteriorate on verbal fluency over 3 years, whereas patients in the other samples did; (2) relatively few patients from the drug trial progressed from MCI to dementia (about 10% after 4 years), in contrast to the other four samples with progression rates over 30%.

CONCLUSION

Conventional MCI criteria were insufficient to allow for the creation of well-defined and internationally comparable samples of MCI patients. More recently published criteria for MCI or "MCI due to AD" are unlikely to remedy this situation. The Alzheimer scientific community needs to agree on a standard set of neuropsychological tests including appropriate selection criteria to make MCI a scientifically more useful concept. Patient data from different sources would then be comparable, and the scientific merits of algorithm-based study designs such as the PGSA could be properly assessed.

摘要

背景

安慰剂组模拟方法(PGSA)旨在部分替代随机安慰剂对照试验(RPCT),利用历史对照组的数据来减少接受长期安慰剂治疗的研究参与者的数量。PGSA 算法用于创建虚拟对照组最初源自阿尔茨海默病神经影像学倡议(ADNI)数据库中的轻度认知障碍(MCI)数据。为了生成更具普遍性的算法,我们旨在以启发式的方式将五个不同的 MCI 数据库汇集在一起,创建一个“标准对照算法”,用于未来的临床试验。

方法

我们比较了来自两个北美队列研究(n=395 和 4328)、一个公司赞助的国际临床药物试验(n=831)和两个方便的患者样本的数据,一个来自德国(n=726),一个来自瑞士(n=1558)。

结果

尽管五个 MCI 样本在纳入和排除标准方面存在差异,但它们的基线人口统计学和认知表现数据差异小于预期。然而,五个样本在随后的认知表现和临床发展方面差异显著:(1)药物试验中的 MCI 患者在 3 年内言语流畅性没有恶化,而其他样本中的患者则恶化;(2)药物试验中从 MCI 进展为痴呆的患者相对较少(4 年后约 10%),而其他四个样本的进展率超过 30%。

结论

传统的 MCI 标准不足以创建定义明确且具有国际可比性的 MCI 患者样本。最近发布的 MCI 或“AD 所致 MCI”标准不太可能改善这种情况。阿尔茨海默病科学界需要就一套标准的神经心理学测试达成一致,包括适当的选择标准,以使 MCI 成为一个更具科学意义的概念。然后,来自不同来源的患者数据将具有可比性,并且可以正确评估基于算法的研究设计(如 PGSA)的科学价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec25/8106156/6e4bf8967668/13195_2021_832_Fig1_HTML.jpg

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