The Personalized Parkinson Project De Novo Cohort
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Parkinson Disease
- Sponsor
- Radboud University Medical Center
- Enrollment
- 103
- Locations
- 1
- Primary Endpoint
- Annual change in digital biomarkers for gait
- Status
- Active, not recruiting
- Last Updated
- last year
Overview
Brief Summary
Currently, the Movement Disorders Society (MDS)-UPDRS scale remains the gold standard to document the outcomes in clinical trials for Parkinson's disease (PD). The MDS-UPDRS is far from infallible, as it is based on subjective scoring (using a rather crude ordinal score), while execution of the tests depends on clinical experience. Not surprisingly, the scale is subject to both significant intra- and inter-rater variability that are sufficiently large to mask an underlying true difference between an effective intervention and placebo. Digital biomarkers may be able to overcome the limitations of the MDS-UPDRS, as they continuously collects real-time data, during the patient's day to day activities. In this study the investigators are interested in developing algorithms to track progression of bradykinesia, gait impairment, postural sway, tremor, physical activity, sleep quality, and autonomic dysfunction (the latter being derived from e.g. skin conductance and changes in heart rate variability).
Detailed Description
This PPP de NOVO cohort aims to validate novel digital biomarkers for disease progression, fostering the unique research infrastructure and data collection protocol that are available. The PPP de NOVO cohort consists of patients with de novo (i.e., newly diagnosed and previously untreated) Parkinson's disease who will be followed longitudinally for two years. De novo patients create the opportunity to study disease progression without interference of pharmacological treatment. The observation of this natural process in the earliest course of the disease is highly relevant for the development disease modifying interventions, which are likely to have the biggest potential in the earliest phases of the disease, when the loss of substantia nigra cells is minimal. In particular, the investigators will deploy the PPP de NOVO cohort for the development of digital biomarkers that could serve as a surrogate or, with time, possibly as key secondary or even a primary outcome in future clinical trials of disease-modifying interventions. Digital biomarkers hold great promise in this regard, as they provide a means to objectively track patients and measure their function in their own living environment, unobtrusively, and over long periods of time. The outcomes are potentially more sensitive than currently available clinical scales, which also be included in the protocol and perhaps also more relevant as they provide an insight into daily life functioning over extended periods of time. The primary objective is to develop novel digital biomarkers that allow for measurement of disease progression in de novo PD patients. Our hypothesis is that digital progression biomarkers will have greater sensitivity and greater power for detecting disease progression than conventional scales. The secondary objective is to test the feasibility of the Proof-Of-Concept (POC) study protocol that UCB (Union Chimique Belge) Pharma will use for their potentially disease modifying treatment. The PPP de NOVO study is considered instrumental in optimizing planning, data acquisition, analysis and interpretation of the digital data collected in the POC study. The third objective of this study is to create an extensive longitudinal dataset describing the clinical and functional characteristics of a representative PD de novo cohort to allow researchers to investigate important unanswered questions in PD.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Subject has Parkinson's disease of ≤2 years of duration, defined as the time since the diagnosis was made by a neurologist.
- •Subject is an adult, at least 18 years of age.
- •Subject can read and understand Dutch.
- •Subject has completed the Informed Consent, as approved by the Institutional Review Board (IRB).
- •Subject is willing, competent, and able to comply with all aspects of the protocol, including follow-up schedule and bio-specimen collection.
- •Subject has never been treated before with any symptomatic dopaminergic drug treatment for Parkinson's disease and is not expected to start treatment for motor symptoms of PD within 52 weeks from baseline.
Exclusion Criteria
- •Subject has co-morbidities that would hamper interpretation of parkinsonian disability, such as coincident musculoskeletal abnormalities, in the opinion of the Investigator.
- •Subject is taking Mucuna Pruriens.
- •For Study Watch: subject is allergic to nickel.
Outcomes
Primary Outcomes
Annual change in digital biomarkers for gait
Time Frame: From baseline till two year follow-up
Identify (a combined set of) gait-related features extracted from wearable sensor data, that are relevant for patients and that are sensitive to disease progression in de novo PD patients. Which outcome and which Unit of Measure for gait will be selected cannot be defined on forehand, as this is part of the analytical approach, as described by Manta et al. (Digital measures of health that matter to patients. Digit Biomark 2020;4:69-77).
Annual change in digital biomarkers for postural sway
Time Frame: From baseline till two year follow-up
Identify (a combined set of) postural sway-related features extracted from wearable sensor data, that are relevant for patients and that are sensitive to disease progression in de novo PD patients. Which outcome and which Unit of Measure for postural sway will be selected cannot be defined on forehand, as this is part of the analytical approach, as described by Manta et al. (Digital measures of health that matter to patients. Digit Biomark 2020;4:69-77).
Annual change in digital biomarkers for tremor
Time Frame: From baseline till two year follow-up
Identify (a combined set of) tremor-related features extracted from wearable sensor data, that are relevant for patients and that are sensitive to disease progression in de novo PD patients. Which outcome and which Unit of Measure for tremor will be selected cannot be defined on forehand, as this is part of the analytical approach, as described by Manta et al. (Digital measures of health that matter to patients. Digit Biomark 2020;4:69-77).
Annual change in digital biomarkers for bradykinesia
Time Frame: From baseline till two year follow-up
Identify (a combined set of) bradykinesia-related features extracted from wearable sensor data, that are relevant for patients and that are sensitive to disease progression in de novo PD patients. Which outcome and which Unit of Measure for bradykinesia will be selected cannot be defined on forehand, as this is part of the analytical approach, as described by Manta et al. (Digital measures of health that matter to patients. Digit Biomark 2020;4:69-77).
Annual change in digital biomarkers for time active vs inactive during the day
Time Frame: From baseline till two year follow-up
Identify (a combined set of) features that reflect the time a person is active and inactive during the day, extracted from wearable sensor data, that are relevant for patients and that are sensitive to disease progression in de novo PD patients. Which outcome and which Unit of Measure for time active vs inactive during the day will be selected cannot be defined on forehand, as this is part of the analytical approach, as described by Manta et al. (Digital measures of health that matter to patients. Digit Biomark 2020;4:69-77).
Annual change in digital biomarkers for skin impedance
Time Frame: From baseline till two year follow-up
Identify (a combined set of) features that reflect skin impedance, extracted from wearable sensor data, that are relevant for patients and that are sensitive to disease progression in de novo PD patients. Which outcome and which Unit of Measure for skin impedance will be selected cannot be defined on forehand, as this is part of the analytical approach, as described by Manta et al. (Digital measures of health that matter to patients. Digit Biomark 2020;4:69-77).
Annual change in digital biomarkers for heart rate variability
Time Frame: From baseline till two year follow-up
Identify (a combined set of) features that reflect heart rate variability, extracted from wearable sensor data, that are relevant for patients and that are sensitive to disease progression in de novo PD patients. Which outcome and which Unit of Measure for heart rate variability will be selected cannot be defined on forehand, as this is part of the analytical approach, as described by Manta et al. (Digital measures of health that matter to patients. Digit Biomark 2020;4:69-77).
Secondary Outcomes
- Compliance to wearing the smartwatch(From baseline till two year follow-up)
- Drop-out rate(From baseline till two year follow-up)
- Change in PRO-Mobility(From baseline till two year follow-up, every 13 weeks)
- Change in PGI-S Mobility(From baseline till two year follow-up, every 13 weeks)
- Change in PRO-Fatigue(From baseline till two year follow-up, every 13 weeks)
- Change in PGI-S Fatigue(From baseline till two year follow-up, every 13 weeks)
- Change in PGI-C Symptoms(From baseline till two year follow-up, every 13 weeks)
- Change in PRO-Functional Slowness(From baseline till two year follow-up, every 13 weeks)
- Change in PGI-S Symptoms(From baseline till two year follow-up, every 13 weeks)
- Perceived feasibility of longitudinal follow-up and repeated assessments(From baseline till two year follow-up)
- Compliance to weekly structured tasks(From baseline till two year follow-up)
- Change in PGI-S Functional Slowness(From baseline till two year follow-up, every 13 weeks)