Assessing Tele-Health Outcomes in Multiyear Extensions of Parkinson's Disease Trials-2 (AT-HOME PD-2)

新冠肺炎疫情扰乱了临床研究，突显了以患者为中心的研究的价值 允许在家中参与并直接从参与者那里收集数据的方法。是这样的 利用视频访问、数字工具和参与者报告的分散式研究可以覆盖大量 地理上分散的参与者人口，增加评价的频率和范围，并减少 参与的负担。帕金森病，一种临床上不同类型的神经退行性疾病， 导致进行性残疾，非常适合这样的模式。传统的评估通常是主观的， 对变化不敏感，仅限于零星的管理，因此未能捕捉到 帕金森氏症。在家帕金森病，最大的正在进行的分散式纵向观察性帕金森氏症 利用数字工具进行的疾病研究，正在远程描述约225名帕金森氏症患者的特征 NINDS资助，3期临床试验，STRATE-PD III和SURE-PD3。这些研究产生了与 全面的临床表型、全基因组测序和系列血浆采集。居家PD 参与者通过视频访问、基于智能手机的评估和在线调查进行表征 站台。该队列现在正在接近帕金森氏症的中期，这为进一步发展提供了机会 我们对这一未被研究的人群的了解，提高了对临床相关疾病的预测 像跌倒和认知障碍这样的里程碑，量化体力活动，识别敏感的远程疾病 措施。该项目将把这一队列的随访延长3年，并扩大数字表型 参与者，使用基于智能手机的评估和两个手腕佩戴的传感器。这个项目的目的是 1)评估数字工具和远程参与者报告可在多大程度上提高预测 临床相关疾病里程碑与传统措施的比较，2)量化 在现实世界中，帕金森病中期的体力活动、采取的步骤和步态，以及3)探索 帕金森病中期患者体力活动与临床结局的关系。我们将生成 一个数据集，其中包含大约10年的PD进展数据，该数据集在使用 多巴胺能药物和进展到帕金森氏症中期及以后。这一丰富的数据集将 通过填补帕金森氏症中期人群的知识空白来加速治疗开发， 帮助优化以患者为中心的远程研究的模型，评估新方法 预测疾病结果，并评估远程结果衡量标准。

The COVID-19 pandemic has disrupted clinical research and highlighted the value of patient centered research methods that enable participation from the home and collection of data directly from participants. Such decentralized research studies that harness video visits, digital tools and participant reporting, can reach a large, geographically dispersed population of participants, increase the frequency and scope of evaluation, and reduce the burden of participation. Parkinson’s disease, a clinically heterogeneous neurodegenerative disorder that causes progressive disability, is well suited to such a model. Traditional assessments are typically subjective, insensitive to change, and limited to episodic administration and therefore fail to capture the complexity of Parkinson’s disease. AT-HOME PD, the largest on-going decentralized longitudinal observational Parkinson’s disease study with digital tools, is remotely characterizing ~225 participants with Parkinson’s disease from two NINDS-funded, phase 3 clinical trials, STEADY-PD III and SURE-PD3. These studies yielded cohorts with comprehensive clinical phenotyping, whole genome sequencing, and serial plasma collection. AT-HOME PD participants are being characterized through video visits, smartphone-based assessments, and an online survey platform. The cohort is now approaching mid-stage Parkinson’s disease, presenting an opportunity to advance our understanding of this under-studied population, improve the prediction of clinically relevant disease milestones like falls and cognitive impairment, quantify physical activity, and identify sensitive remote disease measures. This project will extend the follow-up of this cohort by 3 years and expand digital phenotyping of participants, using smartphone-based assessments and two wrist-worn sensors. The aims of this project are to 1) evaluate the extent to which digital tools and remote participant reporting can improve the prediction of clinically relevant disease milestones compared with traditional measures, 2) quantify longitudinal change in physical activity, steps taken, and gait in mid-stage Parkinson’s disease in the real-world, and 3) explore the relationship between physical activity and clinical outcomes in mid-stage Parkinson’s disease. We will generate a dataset with approximately 10 continuous years of data on PD progression that begins prior to use of dopaminergic medications and progresses to midstage Parkinson’s disease and beyond. This rich dataset will accelerate therapeutic development by filling knowledge gaps in the mid-stage Parkinson’s disease population, helping to optimize models for conducting patient-centered remote research, evaluating new methods for predicting disease outcomes, and evaluating remote outcome measures.