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

COVID-19大流行扰乱了临床研究，并突出了以患者为中心的研究的价值 使家庭参与和直接从参与者收集数据成为可能的方法。等 利用视频访问、数字化工具和参与者报告的分散式研究可以达到很大的， 参与者的地理分布，增加评价的频率和范围， 参与的负担。帕金森病，一种临床异质性神经退行性疾病， 导致渐进性残疾，非常适合这种模式。传统的评估通常是主观的， 对变化不敏感，仅限于间歇性给药，因此无法捕捉 帕金森氏症。AT-HOME PD，最大的正在进行的分散纵向观察帕金森氏症 一项使用数字化工具的疾病研究，正在远程表征来自两个国家的约225名帕金森病参与者。 NINDS资助的3期临床试验，STEADY-PD III和SURE-PD 3。这些研究产生了以下队列 综合临床表型分析、全基因组测序和连续血浆采集。家庭PD 通过视频访问、基于智能手机的评估和在线调查， 平台该队列目前正接近中期帕金森病，这是一个前进的机会。 我们对这一研究不足的人群的了解，提高了对临床相关疾病的预测， 像福尔斯和认知障碍这样的里程碑，量化身体活动，并识别敏感的远程疾病 措施该项目将延长该队列的随访时间3年，并扩大数字表型分析。 参与者，使用基于智能手机的评估和两个腕戴传感器。该项目的目的是 1)评估数字化工具和远程参与者报告可以在多大程度上改善对 与传统测量方法相比，临床相关疾病里程碑，2）量化 身体活动，采取的步骤，和步态在中期帕金森病在现实世界中，和3）探索 中期帕金森病患者体力活动与临床结果之间的关系我们将产生 一个包含大约10个连续年PD进展数据的数据集，开始于使用 多巴胺能药物和进展到中期帕金森病和超越。这个丰富的数据集将 通过填补中期帕金森病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模型，评估新方法， 预测疾病结果，并评估远程结果测量。

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.