Digital Biotyping of FSHD Patients and Controls

An Exploratory, Non-interventional Study to Biotype Patients With Facioscapulohumeral Muscular Dystrophy (FSHD) and Controls Using Digital Technologies

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.

Study Overview

Study Type

Observational

Enrollment (Actual)

58

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Zuid Holland
      • Leiden, Zuid Holland, Netherlands, 2333 CL
        • Centre for Human Drug Research

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

16 years and older (Child, Adult, Older Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

Up to 40 (but at least 20) patients with genetically confirmed FSHD and 20 controls who own and use an Android based smartphone on a daily basis will be included in this study.

Description

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 inclusion criteria

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.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Patients with FSHD
CHDR Monitoring Remotely (MORE) Withings Steel HR Withings Body+ scale Withings Blood Pressure Monitor
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).
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.
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.
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 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).
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.
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.
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

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Social activity
Time Frame: day 1 to day 42 (+/-3 days)
- Voice activation (probability of human voices in proximity)
day 1 to day 42 (+/-3 days)
Social activity
Time Frame: day 1 to day 42 (+/-3 days)
- Phone (length of call, last 3 digits of phone number, number known/unknown)
day 1 to day 42 (+/-3 days)
Social activity
Time Frame: day 1 to day 42 (+/-3 days)
- SMS (amount of characters, last 3 digits of phone number, number known/unknown)
day 1 to day 42 (+/-3 days)
Social activity
Time Frame: day 1 to day 42 (+/-3 days)
- App usage (categories of apps, start time, running in background/foreground)
day 1 to day 42 (+/-3 days)
Social activity
Time Frame: day 1 to day 42 (+/-3 days)
- Light sensor (lm)
day 1 to day 42 (+/-3 days)
Physical activity
Time Frame: day 1 to day 42 (+/-3 days)
- Acceleration
day 1 to day 42 (+/-3 days)
Physical activity
Time Frame: day 1 to day 42 (+/-3 days)
- Gyroscope
day 1 to day 42 (+/-3 days)
Physical activity
Time Frame: day 1 to day 42 (+/-3 days)
- Magnetic field
day 1 to day 42 (+/-3 days)
Physical activity
Time Frame: day 1 to day 42 (+/-3 days)
- Step count
day 1 to day 42 (+/-3 days)
Physical activity
Time Frame: day 1 to day 42 (+/-3 days)
- Google Places
day 1 to day 42 (+/-3 days)
Physical activity
Time Frame: day 1 to day 42 (+/-3 days)
- Relative location
day 1 to day 42 (+/-3 days)
Biometric data collected using the Withings Health platform:
Time Frame: day 1 to day 42 (+/-3 days)

Withings Steel HR smartwatch

- Sleep pattern (time of sleep, sleep phases)

day 1 to day 42 (+/-3 days)
Biometric data collected using the Withings Health platform:
Time Frame: day 1 to day 42 (+/-3 days)

Withings Steel HR smartwatch

-Heart rate data

day 1 to day 42 (+/-3 days)
Biometric data collected using the Withings Health platform:
Time Frame: day 1 to day 42 (+/-3 days)

Withings Steel HR smartwatch

-Physical activity (steps, walking distance)

day 1 to day 42 (+/-3 days)
Withings Body+ scale
Time Frame: day 1 to day 42 (+/-3 days)
Weight (kg)
day 1 to day 42 (+/-3 days)
Withings Body+ scale
Time Frame: day 1 to day 42 (+/-3 days)
Body composition (%)
day 1 to day 42 (+/-3 days)
Withings Blood Pressure Monitor
Time Frame: day 1 to day 42 (+/-3 days)
Systolic blood pressure (mmHg)
day 1 to day 42 (+/-3 days)
Withings Blood Pressure Monitor
Time Frame: day 1 to day 42 (+/-3 days)
Diastolic blood pressure (mmHg)
day 1 to day 42 (+/-3 days)

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

April 14, 2019

Primary Completion (Actual)

October 4, 2019

Study Completion (Actual)

October 4, 2019

Study Registration Dates

First Submitted

July 2, 2019

First Submitted That Met QC Criteria

August 10, 2021

First Posted (Actual)

August 11, 2021

Study Record Updates

Last Update Posted (Actual)

March 9, 2022

Last Update Submitted That Met QC Criteria

March 8, 2022

Last Verified

August 1, 2021

More Information

Terms related to this study

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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