Training Data Collection & AI Development

"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 a larger scale feasibility trial.

A prospective, time series design will be employed, whereby the LifeChamps platform will be deployed for a total of 3 months.

Older patients with a cancer diagnosis 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 in total. A 3-month recruitment period will be allowed, bringing the total study duration to 6 months (from first patient being enrolled until last patient finishing data collection).

AUTH: Patients aged 65 years and above, diagnosed with early-stage breast or prostate cancer will be identified at the Department of Medical Oncology at G. Genimatas General Hospital, "Alma Zois" a non-profit association of women who had experienced breast cancer based in Thessaloniki, Greece and collaborating private clinics. 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.

Region Stockholm : Melanoma survivors aged 65 years and above, who have completed primary treatment within the last 12 months prior to the study, will be identified by our clinical partners within primary and secondary care in Region Stockholm. Online advertisements for the study will also be disseminated and participants may be recruited through LifeChamps partners (e.g. Karolinska Institute) or the Swedish melanoma patient association (Melanomföreningen) which will direct them to an online recruitment form within Region Stockholm. The researchers will then make a follow-up call to confirm interest in study participation. During the contact, the melanoma survivor will be asked to provide their written consent or decline participation and ask for a second contact before his/her final decision. All declining melanoma survivors will be thanked for their time and reassured that their decision will have no impact on their current or future treatment and care. All consenting participants will be reassured that they can withdraw at any time that they desire from the study.

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.
• 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.
• Smart plug: It will be used to collect data about use home appliances and thereby data about active daily living.

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."