Clinical Trial Details
— Status: Active, not recruiting
Administrative data
NCT number |
NCT05990634 |
Other study ID # |
X00568 |
Secondary ID |
GA875329 |
Status |
Active, not recruiting |
Phase |
N/A
|
First received |
|
Last updated |
|
Start date |
March 1, 2023 |
Est. completion date |
November 2023 |
Study information
Verified date |
August 2023 |
Source |
Region Stockholm |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Interventional
|
Clinical Trial Summary
The purpose of this study is to collect data from various sources (PROM / PREM, sensors,
journal data) to train AI based models in the LifeChamps digital platform in a pre-pilot, as
well as partly implement a pilot/feasibility study to examine the applicability of the
digital technology developed in LifeChamps, as well as the usability for patients (cancer
survivors) and health care professionals
Description:
"The LifeChamps project (https://lifechamps.eu/) is creating a digital platform to support
clinical teams to provide more integrated follow-up care to older patients with cancer. The
digital platform will integrate data coming directly from the patient (patient-reported
outcomes and sensor data from wearable devices), from the home environment (home sensors,
weight scales), and from the clinical environment (data routinely collected via the
Electronic Health Record). The digital platform will use big data analytics (machine
learning) to process all data as part of predictive clinical algorithms for frailty and
quality of life for older patients with cancer. Development of each clinical algorithm
requires that the prototype model (or analytics engine) is trained using abundant real-world
data to help consolidate the predictive ability and validity of the algorithms before the
algorithms are deployed in the feasibility trial.
A prospective, time series design will be employed, whereby the LifeChamps platform will be
deployed first during the pre-pilot in a total of 3 months; later in an interrupted time
series feasibility trial during a period of 5 months.
Older patients with a cancer diagnosis (specifically melanoma) will be the target population
for this study. Consecutive sampling will be used, whereby all older patients with cancer who
meet the eligibility criteria will be approached and invited in the study. Each study
participant will be involved in the study for 3 months or 5 months in total respectively. A
3-month recruitment period will be allowed and is overlapping with the two studies, bringing
the total study duration to 6 months (from first patient being enrolled until last patient
finishing data collection).
Patients aged 65 years and above, diagnosed with stage I-III melanoma skin cancer will be
identified from Region Stockholm participating primary care facilities and the Melanoma
patient association (Melanomföreningen) . The patients will be presented with the opportunity
to participate in the study and screened based on the inclusion and exclusion criteria.
Potential participants will be provided with the information sheet and the consent form,
informed that should they decline to participate this will not change their current treatment
and provided the opportunity to ask any questions they may have.
After written informed consent has been provided, the mini-COG will be used to evaluate study
participants' cognitive function and impairment at baseline. The mini-COG consists of a
3-word recall and a clock-drawing test, and can be completed within 5 minutes. A score of
less than 3/5 indicates the need to refer the patient for full cognitive assessment.
The researcher will also arrange for study participants to receive study equipment, i.e. home
sensors, wearable activity sensors, smart weight scale, and mobile app. The researcher will
arrange a suitable time for a home visit to install the home sensors and test functionality.
The researcher will demonstrate use of study equipment to the participant, and reiterate that
support with use of the technology will be available.
Data collection will involve a variety of sources, including the patient (patient-reported
outcomes and sensor data from wearable devices), the home environment (home sensors, weight
scales), and the clinical site (data routinely collected via the Electronic Health Record).
The following technology will be used:
Mobile devices:
Activity tracker wristband (FitBit charge 4). It will be used to passively monitor and
collect data on heart rate, heart rate variability, steps, activity tracking, sleep
monitoring, breathing rate, skin temperature and SpO2.
Smart T-shirt (Move Sense). It will be used to track participants heart rate (HR),
respiration and movement (body position).
Mobile app (SALUMEDIA). It will be used to enable collection of patient-reported outcome
measures (PROMs) and to forward this information along with the data gathered by the activity
tracker and the smart scale to the Raspberry Pi Kit at home.
At home sensors / devices:
LOCS Home sensors: They will be used to monitor participants' daily activities e.g., to track
ambulation and functioning. Study participants will be provided with 4 motion sensors, 1 door
contact sensor, 2 corridor sensors, and a tag device.
Smart Scale (Withings Body+): It will be used to measure weekly body weight, body composition
and body mass index.
Raspberry Pi (RPI) kit: As an edge gateway, RPI is hosting LOCS gateway, Movesense Gateway
and data ingestion service. RPI will enable data collection and edge analytics and transfer
of data to the LIFECHAMPS platform.
Selected study participant clinical and demographic data from the local EHRs will be
collected and loaded onto the LifeChamps analytics engine. The data will be loaded by
technical partners via the LifeChamps dashboard for processing and analysis. Data regarding
recruitment rate (patients consenting / patients approached), participant retention in the
study, reasons for study discontinuation (if offered), participant adherence with technology,
issues with technology and need for troubleshooting will be recorded. These data will (a) be
recorded by local researchers using bespoke 'recording logs' in the form of an Excel
spreadsheet, and (b) remotely monitored and logged by technical partners involved in the
distribution / management of the technology to be used in the trial as described above."