NCT06820008

Brief Summary

Amyotrophic Lateral Sclerosis (ALS), the most common form of Motor Neuron Disease (MND), is a neurodegenerative disease. At present there are limited treatment options for this disease which progressively affects physical function, i.e., the ability to speak, breathe, walk, and perform activities of daily living. ALS is a rare disease, and can present differently amongst individuals, therefore global collaboration is vital to have enough participants in studies to evaluate the effects of new treatments more precisely. There are now many novel technologies that measure physical function which could be used in research studies to allow people with ALS to participate, in-part from home, knowing that they have access to the best clinical trials but with minimal time and travel burden. Their accuracy and the ability/willingness of people with ALS to use them need to be evaluated before they are accepted. One of the traditional measurements used in research is called the ALS Functional Rating Scale -revised (ALSFRS-r) but this measurement has been criticised for being unable to pick up small changes and, in the digital age, outdated. The primary aim of this study is to develop a digital toolkit for more accurate measurement of physical aspects of ALS. It will test new technologies that measure physical function (i.e., walking, speech, swallow, strength, respiration (breathing), dexterity) that can be used by people with ALS in their own home. This study has two aims: Firstly, to test a selection of new digital technologies (in the form of devices, online systems and applications used on smartphones/electronic tablets) that measure physical function (e.g., walking, speech, strength) and assess whether the technologies are easy to use and acceptable both to people with ALS/MND and healthcare professionals. Secondly, to measure how good technologies are at picking up changes in physical function over time and how they compare to older measures that are usually employed by clinicians. This study will recruit 60 people with the ALS form of MND who attend a MND clinic in Dublin, Ireland. The study will run from November 2024 to December 2027 approximately. During this period, each participant will be asked to take part for a duration of 12 months. The study will compare measurements of physical function collected by a researcher in the traditional way, with new ways of measuring the same functions, using technologies that can be used at home by the person with ALS. The experience of people using the technologies at home will be evaluated with interviews and questionnaires. Over the 12-month duration, participants will be assessed in person by members of the research team on 3 occasions. These assessments will be carried out in the clinic setting or can be completed at the participant's home instead if needed. In between the in-person assessments, participants will also do assessments in their own home every week using technologies, either independently or with telephone or video support from a researcher. The technologies that the participant use at home will be matched to the ones that were assigned to them for the in-person assessment at the beginning. Participants will use only technologies that are suited to them. The researcher will talk to participants about which technologies are suitable for them and which they are comfortable to use. Participants coded data collected using the new technologies will be analyzed using established methods and newer methods such as artificial intelligence (AI). AI refers to the ability of computers and digital devices to learn and simulate human intelligence. Machine learning, a field within AI, analyses large data sets to develop models that improve as more data is added. Analysis of participants coded data will be for research purposes only and will not be used for their medical care. Ultimately this study will create new knowledge on the role of technology in physical measurement in MND and how it can be successfully used in future studies to help find effective treatments.

Trial Health

77
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
60

participants targeted

Target at P25-P50 for all trials

Timeline
19mo left

Started Nov 2024

Typical duration for all trials

Geographic Reach
1 country

1 active site

Status
recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

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Study Timeline

Key milestones and dates

Study Progress48%
Nov 2024Dec 2027

Study Start

First participant enrolled

November 21, 2024

Completed
2 months until next milestone

First Submitted

Initial submission to the registry

January 15, 2025

Completed
27 days until next milestone

First Posted

Study publicly available on registry

February 11, 2025

Completed
2.3 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

June 1, 2027

Expected
6 months until next milestone

Study Completion

Last participant's last visit for all outcomes

December 1, 2027

Last Updated

February 11, 2025

Status Verified

January 1, 2025

Enrollment Period

2.5 years

First QC Date

January 15, 2025

Last Update Submit

February 5, 2025

Conditions

Keywords

ALSPrecisionALSDigital technologiesspeechswallowdexteritymobilityrespirationremote measurementMNDoutcome measurement

Outcome Measures

Primary Outcomes (2)

  • Completion of 12-month follow up period

    An adherence percentage will be calculated based on the number of data captures completed by the participant divided by the total target number of data captures multiplied by 100/1.

    12 months per participant

  • System Usability Scale

    A system usability scale (SUS) will be carried out on every technology to assess usability with a sample of 15 patients per technology (except the prototype hand grip ergometer which will have a sample of 5 patients). Responses will be collected once for each remote or prototype technology that the participant uses over the course of the study. The participant will have used the technology at least twice prior to collecting feedback and as such this affects the schedule for the SUS interviews. Technologies that are part of the in-person assessments (Index-eTap and Gaitkeeper) will have their SUS interviews scheduled in Month 3 (second in-person visit). All other technologies will have their SUS interviews carried out at least 2/3 uses via a video call and before 5 months. This is to reduce burden on participants.

    Modality (Month 1), IOPI Trainer (Month 5), Prototype hand grip ergometer (after 2/3 uses), Index-eTap (Month 3), GaitKeeper (Month 3), ActiGraph (Month 3), MIR (Month 5), PCF (Month 3)

Secondary Outcomes (2)

  • Participant withdrawal or death during the study.

    Less than 12 months depending on date of participant withdrawal or death.

  • Semi-structured interview on usability

    Modality (Month 1), IOPI Trainer (Month 5), Prototype hand grip ergometer (after 2/3 uses), Index-eTap (Month 3), GaitKeeper (Month 3), ActiGraph (Month 3), MIR (Month 5), PCF (Month 3)

Study Arms (1)

Patients diagnosed with the Amyotrophic Lateral Sclerosis (ALS) form of Motor Neurone Disease (MND).

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

Recruitment will primarily take place at the MND clinic in a hospital in Dublin, Ireland (Beaumont Hospital). The national support organisation, the Irish Motor Neurone Disease Association (IMNDA), will also share information about the study including contact details for the research team to their clients through their website and quarterly member's newsletter.

You may qualify if:

  • Diagnosis of ALS made by a Neurologist; possible, lab-supported probable, probable or definite as per the revised El Escorial Criteria.
  • Enrolled in the Precision ALS prospective study.
  • Ability to understand participation requirements and provide informed consent to undergo assessments and for data to be used.
  • Willingness to use a smartphone or tablet and to download and use study apps.
  • Age \>18 years
  • Home access to a stable broadband internet connection and willingness to use this for data collection.

You may not qualify if:

  • Diagnosis of a neurological disease other than ALS, active dementia or psychiatric illness that would limit ability to follow the assessment schedule of the study.
  • Other medical condition that would compromise the patient's safety or limit their participation in this study.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Beaumont Hospital

Dublin, Dublin, Ireland

RECRUITING

MeSH Terms

Conditions

Amyotrophic Lateral SclerosisSpeechRespiratory Aspiration

Condition Hierarchy (Ancestors)

Spinal Cord DiseasesCentral Nervous System DiseasesNervous System DiseasesMotor Neuron DiseaseNeurodegenerative DiseasesTDP-43 ProteinopathiesNeuromuscular DiseasesProteostasis DeficienciesMetabolic DiseasesNutritional and Metabolic DiseasesVerbal BehaviorCommunicationBehaviorRespiration DisordersRespiratory Tract DiseasesPathologic ProcessesPathological Conditions, Signs and Symptoms

Study Officials

  • Dara Meldrum, PhD

    University of Dublin, Trinity College

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Dara Meldrum, PhD

CONTACT

Prof. Orla Hardiman, MD

CONTACT

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
PROSPECTIVE
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Associate Professor, Academic Unit of Neurology, Trinity College Dublin

Study Record Dates

First Submitted

January 15, 2025

First Posted

February 11, 2025

Study Start

November 21, 2024

Primary Completion (Estimated)

June 1, 2027

Study Completion (Estimated)

December 1, 2027

Last Updated

February 11, 2025

Record last verified: 2025-01

Data Sharing

IPD Sharing
Will not share

Data will only be analysed by researchers within the Precision ALS partnership within their host institutions in coordination with the local and overall PIs. Data analysis permissions are also governed by the inter-institutional agreement.

Locations