Digital Biotyping of FSHD Patients and Controls

NCT ID: NCT04999735

Last Updated: 2022-03-09

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 58 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2019-04-14
• Study Completion Date: 2019-10-04

Brief Summary

Facioscapulohumeral muscular dystrophy (FSHD) is a devastating progressive muscle dystrophy. There is no treatment. FSHD is generally characterized by asymmetrical weakness and wasting of facial, shoulder girdle and upper arm muscles followed by weakness of muscles of the trunk and lower extremities, but disease severity varies widely between patients. Relatively long periods of stability are interspersed with short periods of potentially steep decline, leading overall to a slow but unpredictable rate of progression. Different genotypes underlying FSHD have been identified, but they result in highly similar phenotypes and at the molecular level converge on undue expression of the transcription factor, DUX4, in skeletal muscle, which is thought to (ultimately) lead to muscle wasting due to inflammation, apoptosis, and oxidative stress. There is no approved treatment, although various companies are engaged in FSHD drug discovery and development aimed in particular at reducing DUX4 expression. Multiple treatment options are currently under development in both preclinical and early clinical stages. However, these efforts face significant challenges in the path to regulatory approval. Because of the slow and variable rate of progression of FSHD, evidencing a significant treatment response will be cumbersome using only the existing measurements of muscle function. The successful development of these investigative treatments for FSHD is therefore highly dependent on the availability of validated disease and treatment biomarkers to monitor disease progression and response to treatment, respectively. To date, no such validated biomarkers exist. This study is important for four reasons: 1. Clinical testing of FSHD drug candidates requires the availability of clinical biomarkers that (a) change relatively rapidly over time; (b) allow for identification of fast progressors; and (c) correlate with "gold standard", but slowly changing, clinical severity and/or functional scores. This study is a first step in that direction as it seeks to explore if the investigational digital technologies described below are able to generate single or composite variables that (cross-sectionally) distinguish FSHD patients from controls. If identified, such variables will be tested as putative clinical FSHD biomarkers in a follow-up longitudinal study with FSHD patients. 2. Patient testimonies indicate that living with FSHD means living with pain, fatigue, social isolation, and anxiety about the future. This study provides the first-ever opportunity to gather objective, real-world data about the impact of FSHD on daily life. 3. Regulators have already indicated that Real-World Data (RWD) is a top strategic priority for their drug reviews. This study aims to fill this gap by gathering RWD about the physical and social activities of FSHD patients in comparison with controls. This way we aim to find (composite) scores that correlate with selected severity and functional scores and additionally distinguish FSHD patients from controls. 4. This study offers an opportunity to expand the spectrum of diseases in which RWD may be used as (a basis for) clinical outcome measures. A successful outcome of this study may support testing the MORE platform in other muscular dystrophies as well.

Conditions

Muscular Dystrophy, Facioscapulohumeral

Study Design

• Observational Model Type: CASE_CONTROL
• Study Time Perspective: CROSS_SECTIONAL

Study Groups

Patients with FSHD

CHDR Monitoring Remotely (MORE) Withings Steel HR Withings Body+ scale Withings Blood Pressure Monitor

CHDR Monitoring Remotely (MORE)

Intervention Type: BEHAVIORAL

CHDR MORE is a highly customizable platform which allows remote monitoring of patients and trial subjects, data ingestion, and data management. The current infrastructure includes an Android app to unobtrusively collect data from smartphone sensors, and a connection to the Withings Health online platform to collect wearable data. Data is stored on a secure server in a structured data scheme ensuring clear data management processes, forming a prerequisite for comprehensive data analysis. The Android app enables data collection from multiple smartphone sensors (e.g. location data, accelerometer and ambient light) as well as phone usage logs (e.g. app usage, calls and texts).

Withings Steel HR

Intervention Type: BEHAVIORAL

The Withings Steel HR is a commercially available smartwatch that combines various sensors to measure activity (steps, sleep, etc.) and heart rate (HR). HR is measured using a PPG (photoplethysmogram, i.e. optically obtained volumetric measurement) based on a commercially available sensor (AS7000) incorporating low-noise and high-sensitivity analogue circuitry. The manufacturer supplies the algorithm for converting the PPG signal into HR values. Data is transferred from the watch to the smartphone using the Withings Health Mate app from where it will be uploaded to the output server.

Withings Body+ scale

Intervention Type: BEHAVIORAL

Body composition (weight, BMI and Skeletal Muscle Mass) can be assessed with the Withings Body+ smart scale at home. A smart phone is required to store data and send collected data to the output server. The device does not require charging.

Withings Blood Pressure Monitor

Intervention Type: BEHAVIORAL

Blood pressure can be assessed with the automated Withings Blood Pressure Monitor at home. A smart phone is required to store data and send collected data to the output server. The device does not require charging

Healthy controls

CHDR Monitoring Remotely (MORE) Withings Steel HR Withings Body+ scale Withings Blood Pressure Monitor

CHDR Monitoring Remotely (MORE)

Intervention Type: BEHAVIORAL

CHDR MORE is a highly customizable platform which allows remote monitoring of patients and trial subjects, data ingestion, and data management. The current infrastructure includes an Android app to unobtrusively collect data from smartphone sensors, and a connection to the Withings Health online platform to collect wearable data. Data is stored on a secure server in a structured data scheme ensuring clear data management processes, forming a prerequisite for comprehensive data analysis. The Android app enables data collection from multiple smartphone sensors (e.g. location data, accelerometer and ambient light) as well as phone usage logs (e.g. app usage, calls and texts).

Withings Steel HR

Intervention Type: BEHAVIORAL

The Withings Steel HR is a commercially available smartwatch that combines various sensors to measure activity (steps, sleep, etc.) and heart rate (HR). HR is measured using a PPG (photoplethysmogram, i.e. optically obtained volumetric measurement) based on a commercially available sensor (AS7000) incorporating low-noise and high-sensitivity analogue circuitry. The manufacturer supplies the algorithm for converting the PPG signal into HR values. Data is transferred from the watch to the smartphone using the Withings Health Mate app from where it will be uploaded to the output server.

Withings Body+ scale

Intervention Type: BEHAVIORAL

Body composition (weight, BMI and Skeletal Muscle Mass) can be assessed with the Withings Body+ smart scale at home. A smart phone is required to store data and send collected data to the output server. The device does not require charging.

Withings Blood Pressure Monitor

Intervention Type: BEHAVIORAL

Blood pressure can be assessed with the automated Withings Blood Pressure Monitor at home. A smart phone is required to store data and send collected data to the output server. The device does not require charging

Interventions

CHDR Monitoring Remotely (MORE)

CHDR MORE is a highly customizable platform which allows remote monitoring of patients and trial subjects, data ingestion, and data management. The current infrastructure includes an Android app to unobtrusively collect data from smartphone sensors, and a connection to the Withings Health online platform to collect wearable data. Data is stored on a secure server in a structured data scheme ensuring clear data management processes, forming a prerequisite for comprehensive data analysis. The Android app enables data collection from multiple smartphone sensors (e.g. location data, accelerometer and ambient light) as well as phone usage logs (e.g. app usage, calls and texts).

Intervention Type: BEHAVIORAL

Withings Steel HR

The Withings Steel HR is a commercially available smartwatch that combines various sensors to measure activity (steps, sleep, etc.) and heart rate (HR). HR is measured using a PPG (photoplethysmogram, i.e. optically obtained volumetric measurement) based on a commercially available sensor (AS7000) incorporating low-noise and high-sensitivity analogue circuitry. The manufacturer supplies the algorithm for converting the PPG signal into HR values. Data is transferred from the watch to the smartphone using the Withings Health Mate app from where it will be uploaded to the output server.

Intervention Type: BEHAVIORAL

Withings Body+ scale

Body composition (weight, BMI and Skeletal Muscle Mass) can be assessed with the Withings Body+ smart scale at home. A smart phone is required to store data and send collected data to the output server. The device does not require charging.

Intervention Type: BEHAVIORAL

Withings Blood Pressure Monitor

Blood pressure can be assessed with the automated Withings Blood Pressure Monitor at home. A smart phone is required to store data and send collected data to the output server. The device does not require charging

Intervention Type: BEHAVIORAL

Eligibility Criteria

Inclusion Criteria

Patients eligible for inclusion in this study have to fulfill all of the following criteria:

1. Written informed consent is obtained before any assessment is performed.

2. Males and females age 16+ years.

3. Genetically confirmed FSHD.

4. Symptomatic as demonstrated by Lamperti score >0.

5. Fully functioning Android-based smartphone with Android version 5.0 or higher.

6. Able to comply with the study procedures, prohibitions and restrictions (drug use) as specified in the protocol.

Controls eligible for inclusion in this study have to fulfill all of the following criteria:

1. Written informed consent is obtained before any assessment is performed.

2. Males and females age 16+ years.

3. Unrelated subjects without FSHD.

4. Fully functioning Android-based smartphone with Android version 5.0 or higher.

5. Able to comply with the study procedures, prohibitions and restrictions (drug use) as specified in the protocol.

Exclusion Criteria

Patients fulfilling any of the following criteria are not eligible for inclusion in this study:

1. Current or previously diagnosed illness or any clinical condition that, in the opinion of the investigator, might confound the results of the study.

2. Positive urine β-human chorionic gonadotropin (β-hCG) pregnancy test at Screening in women of childbearing potential.

3. Wearing a pacemaker or other internal medical device (e.g. Vagus nerve stimulation (VNS), Deep Brain Stimulation (DBS)).

4. Current enrollment in an interventional study.

Controls fulfilling any of the following criteria are not eligible for inclusion in this study:

1. Current or previously diagnosed illness or any clinical condition that, in the opinion of the investigator, might confound the results of the study.

2. Positive urine β-human chorionic gonadotropin (β-hCG) pregnancy test at Screening in women of childbearing potential.

3. Wearing a pacemaker or other internal medical device (e.g. Vagus nerve stimulation (VNS), Deep Brain Stimulation (DBS)).

4. Current enrollment in an interventional study.

• Minimum Eligible Age: 16 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Facio Therapeutics

UNKNOWN

Sponsor Role: collaborator

Centre for Human Drug Research, Netherlands

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

Centre for Human Drug Research

Leiden, South Holland, Netherlands

Countries

Netherlands

References

Zhuparris A, Maleki G, Koopmans I, Doll RJ, Voet N, Kraaij W, Cohen A, van Brummelen E, De Maeyer JH, Groeneveld GJ. Smartphone and Wearable Sensors for the Estimation of Facioscapulohumeral Muscular Dystrophy Disease Severity: Cross-sectional Study. JMIR Form Res. 2023 Mar 15;7:e41178. doi: 10.2196/41178.

Reference Type: DERIVED

PMID: 36920465 (View on PubMed)

Maleki G, Zhuparris A, Koopmans I, Doll RJ, Voet N, Cohen A, van Brummelen E, Groeneveld GJ, De Maeyer J. Objective Monitoring of Facioscapulohumeral Dystrophy During Clinical Trials Using a Smartphone App and Wearables: Observational Study. JMIR Form Res. 2022 Sep 13;6(9):e31775. doi: 10.2196/31775.

Reference Type: DERIVED

PMID: 36098990 (View on PubMed)

Other Identifiers

NL69288.056.19

Identifier Type: OTHER

Identifier Source: secondary_id

CHDR1861

Identifier Type: -

Identifier Source: org_study_id