Design and results of a smartphone-based digital phenotyping study to quantify ALS progression
Design and results of a smartphone-based digital phenotyping study to quantify ALS progression
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DOI：
10.1002/acn3.770
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发表时间：
2019-05-01
影响因子：
5.3
通讯作者：
Onnela, Jukka Pekka
中科院分区：
文献类型：
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作者：
Berry, James D.;Paganoni, Sabrina;Onnela, Jukka Pekka
目的肌萎缩侧索硬化（ALS）临床试验结局指标是基于临床的。主动和被动智能手机数据可以提供有关临床外ALS进展的重要纵向信息。我们使用Beiwe，一个基于智能手机的数字表型研究平台，收集ALS患者大约24周的主动（自我报告ALSFRS-R调查和语音记录）和被动（电话传感器和日志）数据。在诊所，在基线和每3个月，我们收集了肺活量，ALSFRS-R，和ALS-CBS在登记，第12周，第24周。我们还在第6周通过电话收集ALSFRS-R。结果基线时门诊ALSFRS-R与智能手机自我报告的相关系数为0.93（P < 0.001）。基于智能手机的自我报告的ALSFRS-R斜率相当，受试者内标准差较小（0.26 vs. 0.56）。使用Beiwe提供了每周收集的语音样本进行各种分析，我们发现平均停顿时间增加了0.02秒，每个月的样本。解释ALS患者基于智能手机的数字表型分析是可行的和信息丰富的。自我管理的智能手机ALSFRS-R评分与基于临床的ALSFRS-R评分高度相关，变异性低，可用于临床试验。需要更多的研究来全面分析语音记录和被动数据，并确定用于未来ALS临床试验的最佳数字标记。
Objective The amyotrophic lateral sclerosis (ALS) trial outcome measures are clinic based. Active and passive smartphone data can provide important longitudinal information about ALS progression outside the clinic. Methods We used Beiwe, a research platform for smartphone-based digital phenotyping, to collect active (self-report ALSFRS-R surveys and speech recordings) and passive (phone sensors and logs) data from patients with ALS for approximately 24 weeks. In clinics, at baseline and every 3 months, we collected vital capacity, ALSFRS-R, and ALS-CBS at enrollment, week 12, and week 24. We also collected ALSFRS-R by telephone at week 6. Results Baseline in-clinic ALSFRS-R and smartphone self-report correlation was 0.93 (P < 0.001). ALSFRS-R slopes were equivalent and within-subject standard deviation was smaller for smartphone-based self-report (0.26 vs. 0.56). Use of Beiwe afforded weekly collection of speech samples amenable to a variety of analyses, and we found mean pause time to increase by 0.02 sec per month across the sample. Interpretation Smartphone-based digital phenotyping in people with ALS is feasible and informative. Self-administered smartphone ALSFRS-R scores correlate highly with clinic-based ALSFRS-R scores, have low variability, and could be used in clinical trials. More research is required to fully analyze speech recordings and passive data, and to identify optimal digital markers for use in future ALS clinical trials.