Shoulson Ira, Arbatti Lakshmi, Hosamath Abhishek, Eberly Shirley W, Oakes David
Department of Neurology, University of Rochester, Rochester, NY, USA.
Grey Matter Technologies, Inc., Longboat Key, FL, USA.
J Parkinsons Dis. 2022;12(6):1969-1978. doi: 10.3233/JPD-223274.
The Parkinson's Disease Patient Report of Problems (PD-PROP) captures the problems and functional impact that patients report verbatim. Online research participation and advances in language analysis have enabled longitudinal collection and classification of symptoms as trial outcomes.
Analyze verbatim reports longitudinally to examine postural-instability symptoms as 1) precursors of subsequent falling and 2) newly occurring symptoms that could serve as outcome measures in randomized controlled trials.
Problems reported by >25,000 PD patients in their own words were collected online in the Fox Insight observational study and classified into symptoms by natural language processing, clinical curation, and machine learning. Symptoms of gait, balance, falling, and freezing and associated reports of having fallen in the last month were analyzed over three years of longitudinal observation by a Cox regression model in a cohort of 8,287 participants. New onset of gait, balance, falling, and freezing symptoms was analyzed by Kaplan-Meier survival techniques in 4,119 participants who had not previously reported these symptoms.
Classified verbatim symptoms of postural instability were significant precursors of subsequent falling among participants who were older, female, and had longer PD duration. New onset of symptoms steadily increased and informed sample size estimates for clinical trials to reduce the onset of these symptoms.
The tools to analyze symptoms reported by PD patients in their own words and capacity to enroll large numbers of research participants online support the feasibility and statistical power for conducting randomized clinical trials to detect effects of therapeutic interventions.
帕金森病患者问题报告（PD - PROP）记录了患者逐字报告的问题及其功能影响。在线研究参与和语言分析的进展使得能够纵向收集症状并将其分类作为试验结果。
纵向分析逐字报告，以检查姿势不稳症状，一是作为后续跌倒的先兆，二是作为随机对照试验中可作为结果指标的新出现症状。
在福克斯洞察观察性研究中，在线收集了25000多名帕金森病患者用自己的语言报告的问题，并通过自然语言处理、临床整理和机器学习将其分类为症状。在8287名参与者的队列中，通过Cox回归模型对三年纵向观察中的步态、平衡、跌倒、冻结症状以及过去一个月内跌倒的相关报告进行了分析。在4119名此前未报告过这些症状的参与者中，通过Kaplan - Meier生存技术分析了步态、平衡、跌倒和冻结症状的新发情况。
姿势不稳的分类逐字症状在年龄较大、女性且帕金森病病程较长的参与者中是后续跌倒的重要先兆。症状的新发情况稳步增加，并为减少这些症状发作的临床试验提供了样本量估计依据。
分析帕金森病患者用自己的语言报告的症状的工具以及在线招募大量研究参与者的能力，支持了进行随机临床试验以检测治疗干预效果的可行性和统计效力。
