LifeChamps Feasibility Study

Study Overview
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Brief Summary
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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

Detailed Description
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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.

Official Title
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LIFECHAMPS: A Collective Intelligence Platform to Support Cancer Champions - Stockholm Pilot Use Case 2

Conditions
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Melanoma (Skin)

Intervention / Treatment
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* Device: LifeChamps Platform


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Diagnosed with malignant melanoma (stage I-III) and undergone primary treatment within the last 36 months. Has completed primary and secondary cancer treatment and is now in remission (survivorship stage). Assessed as physically and mentally able to participate in the study Can read, write and understand the Swedish language Can bring and use their own smart phone (Android version 10 or newer) below the study Have 24-hour access to internet (broadband) via WiFi router in your own household and/or free 4G mobile data (sim card and 4G router will be provided if this criterion is not met) Exclusion Criteria: Terminal cancer stage or prognosis <18 months from time of recruitment Diagnosed with severe mental illness or cognitive illness that affects the ability to participate Screening with Mini-Cog where the result is between 0-2 Inability or unwillingness to provide written informed consent

Ages Eligible for Study
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Minimum Age: 65 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Supportive Care
Intervention Model: Single Group Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: LifeChamps Platform<br>Participants will be asked to use the LifeChamps platform and will be provided with the study equipment (sensors/home kit). | Device: LifeChamps Platform<br>* Participants will be provided with the study equipment, i.e., a mobile app, smartwatch, smart t-shirt, smart scale, location home sensor, and a micro-computer, with which they will need to interact with the devices for three months in the respective study phase (pre-pilot/feasibility trial). Specifically, participants should wear the activity tracker wristband (Fitbit Charge 4) as much as possible. The smart t-shirt should as well be worn daily as much as possible. Additionally, participants should use the smart scale to weigh themselves and the mobile app to fill in selected PROMs monthly, while the ambient home sensors (location home sensor (LOCS) and smart plug) will be passively collecting information about their everyday living during these three months. Lastly, participants' clinical and demographic data from the local EHRs will be collected.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Analytical models | The collected data will be used to train and test the analytical models. For example, the initial data from sensors will be refined, further, with statistical, spectral and supervised learning analyses to identify and extract possible patterns (e.g., activities of daily living) inside their signals. Sensor, EHR and PROM data will be all analysed together through exploratory algorithms (e.g., pairwise Markov random fields, Bayesian networks) to identify possible interactions and dependencies among their trajectories, mapping the frailty and QOL domains of elderly melanoma cancer patients across all the data collection process. | 3 to 6 Months | 
| Usability assessment | The usability of the LifeChamps platform will be measured through the System Usability Scale questionnaire with Likert type questions from 1 to 5, where 5 is strongly agree and 1 is strongly disagree on the ten statements of the SUS questionnaire. | 3 to 6 Months | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| QoL assessment | Quality of life assessment as measured by LASA via 0-10 Likert scales, with 10 being the best. | 3 to 6 Months | 
| Fear of Cancer Recurrency (FCRI) | PROM assesment of the FCRI Short Form 9-item questionnaire (Simard, S; Savard, J; 2015) | 3 to 6 Months | 
| Sun Exposure and Protection Index (SEPI) | Assessment as measured by SEPI via 0-4 point Likert scales. | 3 to 6 Months | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Quality of Life, Melanoma, Cancer, Survivorship, mHealth application, Wearables, Artificial Intelligence