Development of Digital Therapeutics Algorithms for Personalized Parkinson's Disease Treatment and Medication Plan Optimization
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 54
- 试验地点
- 3
- 主要终点
- Performance of the machine learning algorithm in predicting patient-reported symptom scores based on accelerometer data collected during in-clinic visits and home-based unsupervised data collected over 6 months
研究概览
简要总结
The study is aimed at developing Digital Therapeutics (DTx) algorithms for personalized PD treatment and medication plan optimization, based on Real World Data (RWD) collected from patients via digital mobile app and wearable sensors.
The study design is observational/noninterventional, prospective, single-arm, aimed at collecting data from wearable sensors for validation of symptom detection algorithms, through (1) a supervised in-clinic motor assessment, performed using validated clinical scales (Visit 3, Visit 4), and (2) an unsupervised, home-based, 6-month (Visit 3 to Visit 4) data collection from wearable devices (passive monitoring) for algorithm cross-validation using patient reported outcomes (PROMs) and remote clinical assessments. The devices used in the study will be a commercial smartwatch (Garmin Vivosmart 5) for inertial data collection and a digital application through which subjects will report PROMs via a digital symptom diary. Screening visits (Visit 1 and Visit 2) will be conducted prior to enrollment to verify eligibility criteria through clinical assessments, the subjects' symptom diary, and by assessing adherence to the use of the study tools provided (i.e., mobile application and smartwatch).
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Written informed consent (IC) obtained.
- •Age > 18 years.
- •Male or female patients Meeting the MDS clinical diagnostic criteria for Parkinson's Disease (Postuma et al., 2015)
- •At least one motor symptoms OFF-period each day, excluding early morning akinesia.
- •On treatment with Levodopa
- •Stable Levodopa regimen for 4 weeks before Screening Visit;
- •Levodopa Equivalent Daily Dose (LEDD) > 400 mg, AND/OR Levodopa Intake > 2 administration/day;
- •The subject is willing and able to attend study procedures and to use wearable and mobile devices.
排除标准
- •Secondary or atypical PD.
- •Cognitive problems which significantly impair his/her ability to give an IC and perform the study tasks.
- •Levodopa Equivalent Daily Dose (LEDD) > 800 mg, AND/OR Levodopa intake > 8 administration/day;
- •Any condition that in the opinion of the investigator would interfere with the interpretation of the study results or constitute a health risk for the subject if he/she takes part in the study.
- •Concomitant participation to clinical trials with investigational medicinal products.
- •Failure to show, in opinion of the investigator, acceptable/appropriate use of wearable and mobile device (e.g. weekly average daily wearable wear time < 8 hours).
- •Having an advanced treatment (including Deep Brain Stimulation, Apomorphine, Duodopa), is not an exclusion criterion, as well as the subject decision or capability to attend the exercise and speech training programs within the mobile app.
研究组 & 干预措施
Arm 1
The study group will receive noninvasive, in-depth clinical assessments similar in frequency to monitoring pertinent to normal clinical practice aimed at people with Parkinson's disease. In addition, within the mobile application provided as a gateway for data collection from the wearable sensors, subjects will also have the ability to access a library of video-recorded exercises, the effect of which on symptom modification, however, is not the subject of this investigation.
干预措施: Smartwatch Garmin Vivosmart [wearable sensor] (Device)
Arm 1
The study group will receive noninvasive, in-depth clinical assessments similar in frequency to monitoring pertinent to normal clinical practice aimed at people with Parkinson's disease. In addition, within the mobile application provided as a gateway for data collection from the wearable sensors, subjects will also have the ability to access a library of video-recorded exercises, the effect of which on symptom modification, however, is not the subject of this investigation.
干预措施: Soturi™ [digital mobile app] (Device)
Arm 1
The study group will receive noninvasive, in-depth clinical assessments similar in frequency to monitoring pertinent to normal clinical practice aimed at people with Parkinson's disease. In addition, within the mobile application provided as a gateway for data collection from the wearable sensors, subjects will also have the ability to access a library of video-recorded exercises, the effect of which on symptom modification, however, is not the subject of this investigation.
干预措施: Clinical Assessment (Other)
结局指标
主要结局
Performance of the machine learning algorithm in predicting patient-reported symptom scores based on accelerometer data collected during in-clinic visits and home-based unsupervised data collected over 6 months
时间窗: Baseline to Week 26
To develop and test machine learning model's performance outcome in predicting patient-reported symptom scores. The specific outcome metrics and the respective units used to evaluate the models cannot be defined in advance, as they will depend on the nature of the data and the method of analysis as described by Giannakopoulou,et al. 2022 (Internet of Things Technologies and Machine Learning Methods for Parkinson's Disease Diagnosis, Monitoring and Management: A Systematic Review. Sensors, 22(5), 1799)
Change in patient-reported motor symptoms, as measured by an electronic symptoms diary, from baseline to the 6-month follow-up visit.
时间窗: Baseline to Week 26
"Change in Patient-Reported Motor Symptoms" focuses on assessing changes in motor symptoms reported by patients using an electronic symptoms diary, from baseline to the 6-month follow-up visit. Patients self-report their motor symptoms through the electronic diary, which allows them to record their symptoms and their severity, duration, and frequency.
Change in MDS-UPDRS Part III score from baseline to the 6-month follow-up visit, as measured during in-clinic visits.
时间窗: Baseline to Week 26
Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III includes 33 items to assess severity of motor symptoms, scoring per each item goes from 0= normal, 1 = slight, 2 = mild, 3 = moderate, and 4 = severe. Total score ranges from 0 to 132.
Performance of the machine learning algorithm in predicting MDS-UPDRS Part III scores based on accelerometer data collected during in-clinic visits and home-based unsupervised data collected over 6 months.
时间窗: Baseline to Week 26
To develop and test machine learning model's performance outcome in predicting the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III motor symptoms scores.The specific outcome metrics and the respective units used to evaluate the models cannot be defined in advance, as they will depend on the nature of the data and the method of analysis as described by Giannakopoulou,et al. 2022 (Internet of Things Technologies and Machine Learning Methods for Parkinson's Disease Diagnosis, Monitoring and Management: A Systematic Review. Sensors, 22(5), 1799)
次要结局
- Change in Levodopa Medication Plan: Units(Baseline to Week 26)
- Change in Motor Symptoms Digital Biomarkers: duration(Baseline to Week 26)
- Change in Motor Symptoms Digital Biomarkers: frequency(Baseline to Week 26)
- Change in ePROMs: symptoms severity(Baseline to Week 26)
- Change in ePROMs, reported symptoms duration(Baseline to Week 26)
- Change in Levodopa Medication Plan: Medication Dose Strength(Baseline to Week 26)
- Change in MDS-UPDRS Total Score and sub-scale total scores (Parts I-II-IV)(Baseline to Week 26)
- Change in PDQ-39 Total Score(Baseline to Week 26)
- Change in Motor Symptoms Digital Biomarkers: severity(Baseline to Week 26)
- Change in Levodopa and Dopamine-Agonist Equivalent Daily Dosages (LEDD, DAEDD)(Baseline to Week 26)
- Change in Medication Levodopa Plan: Frequency of Intakes(Baseline to Week 26)
- Digital Biomarkers: Activity(Baseline to Week 26)
- Change in ePROMs: symptoms frequency(Baseline to Week 26)