Identifying best methods for the detection of subtle cognitive decline

确定检测微妙认知能力下降的最佳方法

• 批准号: 10328956
• 负责人: Kelsey R Thomas
• 金额: $ 15.8万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-15 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10328956
• 关键词: Alzheimer' s Disease; Alzheimer' s disease model; Alzheimer' s disease pathology; Alzheimer' s disease related dementia; Alzheimer’s disease biomarker; Amyloid; Applications Grants; Archives; Area; Attention; Biological Markers; Classification; Clinical; Clinical Trials; Cognitive; Cost Savings; Data; Data Set; Dementia; Diagnosis; Disease; Early Diagnosis; Early Intervention; Early identification; Family; Future; Gold; Hippocampus (Brain); Impaired cognition; Individual; Long-Term Care; Measures; Medical; Memory; Methods; Nerve Degeneration; Neuropsychology; Outcome Measure; Participant; Pathogenesis; Pathologic; Pathologic Processes; Patient Self-Report; Patients; Performance; Persons; Phase; Positron-Emission Tomography; Predictive Value; Prevention; Questionnaires; Reporting; Research; Research Personnel; Research Project Grants; Risk; Savings; Scoring Method; Testing; White Matter Hyperintensity; Work; accurate diagnosis; base; care costs; classification algorithm; clinical care; cognitive change; cognitive performance; cost; cost efficient; depressive symptoms; design; detection method; experience; functional decline; functional disability; improved; informant; mild cognitive impairment; neuroimaging; next generation; open source; pre-clinical; prognostic value; programs; progression marker; prospective; recruit; rural area; screening; statistics; tau Proteins; tool

PROJECT SUMMARY / ABSTRACT New submission for PAS-19-391 (Small Research Grant Program for the Next Generation of Researchers in AD/ADRD Research: Area of Focus Archiving and Leveraging Existing Data Sets for Analyses [R03]). Recent statistics show that if everyone alive in 2018 who will develop Alzheimer’s disease (AD) had early and accurate diagnosis, there would be a savings of $7.9 trillion in medical and long-term care costs. Although the advent of Alzheimer’s disease (AD) biomarkers has revolutionized our understanding of AD pathogenesis during the preclinical phase, these approaches are often expensive, invasive, inaccessible due to rural location, cost, or medical contraindications. Additionally, beyond a focus on AD biomarkers alone, it is essential to emphasize that cognitive difficulties and subsequent functional impairment are the features of the disease that negatively impact the lives of patients and their families. Emerging evidence suggests that subtle cognitive changes may develop much earlier than originally described in models of AD and these subtle cognitive changes add meaningful prognostic value, above and beyond AD biomarkers, in predicting progression to mild cognitive impairment (MCI) and dementia. The gold standard approach for identifying subtle cognitive decline in preclinical AD, however, remains unclear. Therefore, we propose to apply four different classification algorithms for subtle cognitive decline in the open source Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. The four classifications methods include two subjective approaches: self-reported subjective cognitive decline (Self-SCD) and informant-reported subjective cognitive decline (Inform-SCD); and two objective approaches: a sensitive neuropsychological individual test-based approach called objectively-defined subtle cognitive decline (Obj-SCD) and a composite score-based approach using the preclinical Alzheimer’s cognitive composite to identify subtle cognitive decline (PACC-SCD). The specific aims of this proposal include: 1) Compare AD biomarkers across 4 subtle cognitive decline definitions (Self-SCD, Inform-SCD, Obj-SCD, and PACC-SCD); 2) Determine which subtle cognitive decline definitions best capture objective cognitive decline in the year preceding the subtle cognitive decline classification; and 3) Examine longitudinal a) clinical and b) biomarker progression across subtle cognitive decline definitions to determine the definitions with the best predictive utility. Results of the proposed aims will likely impact the design of future studies, as having simple, yet reliable, and highly cost- efficient methods for narrowing the initial pool of participants so that only those at greatest risk require a PET scan for screening purposes would result in significant cost-savings. Additionally, these results will serve as critical preliminary data for future grant applications, and be a key step toward improving clinically meaningful early detection methods of those at risk for future decline, particularly those with limited access to AD biomarker testing.

项目总结/摘要 PAS-19-391（美国下一代研究人员小额研究资助计划） AD/ADRD研究：重点领域和利用现有数据集进行分析[R 03]）。 最近的统计数据显示，如果每个人都活在2018年谁将发展老年痴呆症（AD）早 和准确的诊断，将节省7.9万亿美元的医疗和长期护理费用。虽然 阿尔茨海默病（AD）生物标志物的出现彻底改变了我们对AD发病机制的理解 在临床前阶段，这些方法通常是昂贵的、侵入性的、由于农村位置而难以获得的， 成本或医疗禁忌症。此外，除了关注AD生物标志物之外， 强调认知困难和随后的功能障碍是疾病的特征， 对患者及其家人的生活产生负面影响。新的证据表明，微妙的认知 这些变化可能比最初在AD模型中描述的要早得多， 在预测进展为轻度认知障碍方面， 轻度认知障碍（MCI）和痴呆。识别临床前患者轻微认知功能下降的金标准方法 然而，AD仍然不清楚。因此，我们提出了四种不同的分类算法， 认知能力下降在开源阿尔茨海默病神经成像倡议（ADNI）数据集。四 分类方法包括两种主观方法：自我报告的主观认知下降（自我SCD） 和线人报告的主观认知下降（Inform-SCD）;和两个客观的方法：一个敏感的 客观定义的微妙认知下降（Obj-SCD） 以及一种基于综合评分的方法，使用临床前阿尔茨海默氏症认知综合征来识别细微的 认知功能减退（PACC-SCD）。该提案的具体目的包括：1）比较4种AD生物标志物 微妙的认知衰退定义（Self-SCD、Inform-SCD、Obj-SCD和PACC-SCD）; 2）确定 轻微认知衰退的定义最好地捕捉了在轻微认知衰退前一年的客观认知衰退。 认知下降分类;和3）检查纵向a）临床和B）生物标志物进展， 微妙的认知衰退定义，以确定具有最佳预测效用的定义。结果 拟议的目标可能会影响未来研究的设计，因为它简单、可靠、成本高- 有效的方法来缩小参与者的初始池，使只有那些在最大的风险需要PET 为筛查目的进行扫描将节省大量费用。此外，这些结果将作为 为未来的拨款申请提供关键的初步数据，并成为改善临床意义的关键一步。 早期检测那些有未来衰退风险的人的方法，特别是那些获得AD生物标志物有限的人 试验.