The Personalized Parkinson Project De Novo Cohort

NCT ID: NCT04985539

Last Updated: 2025-03-24

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ACTIVE_NOT_RECRUITING

Total Enrollment

103 participants

Study Classification

OBSERVATIONAL

Study Start Date

2020-08-29

Study Completion Date

2025-12-31

Brief Summary

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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

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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.

Conditions

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Parkinson Disease Parkinsonian Disorders Basal Ganglia Diseases Brain Diseases Central Nervous System Diseases Nervous System Diseases Movement Disorders Neurodegenerative Diseases

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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PD de novo

Observational.

Verily Study Watch

Intervention Type DEVICE

Participants wear the Verily Study Watch for 2 years, for longitudinal data collection.

Interventions

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Verily Study Watch

Participants wear the Verily Study Watch for 2 years, for longitudinal data collection.

Intervention Type DEVICE

Eligibility Criteria

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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.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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UCB Pharma

INDUSTRY

Sponsor Role collaborator

Verily Life Sciences LLC

INDUSTRY

Sponsor Role collaborator

Radboud University Medical Center

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Bastiaan R Bloem, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

Radboud University Medical Center

Locations

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Radboud University Medical Center

Nijmegen, , Netherlands

Site Status

Countries

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Netherlands

Other Identifiers

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NL72631.091.20

Identifier Type: -

Identifier Source: org_study_id

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