Neoplasms

Urinary Tract, Sexual Organs, and Pregnancy Conditions

All Conditions

Skin and Connective Tissue Diseases

Prostatic Neoplasms

Breast Neoplasms

Genital Neoplasms, Male

Urogenital Neoplasms

Genital Diseases

Genital Diseases, Male

Urogenital Diseases

Prostatic Diseases

Male Urogenital Diseases

Participants will be asked to use the LifeChamps platform and will be provided with the study equipment.

Participating Healthcare professionals will be asked to use the LifeChamps Dashboard

Healthcare professionals that will participate in the study will be introduced will have access to the LifeChamps Dashboard, which will display the data monitored from the patients, thus potentially facilitating patients' follow-up between clinical consultations. The LC Dashboard will provide pseudonymised information regarding the patients' physical activity and PROMs for the purpose of the pilot feasibility trial. They will not be able to view real time processed information, such as risk of frailty, QoL, risk of dependency and psychological condition, from the LIFECHAMPS analytics engine. They will be shown the anonymised outputs of the engine per patient and asked their opinions on the usability, acceptability and on whether such information would have helped better manage their patients' supportive care.

LifeChamps Platform HCP

Participants will be asked to provide 5 endpoints (PROMS) and will be provided with the study equipment, i.e., a mobile app, smartwatch, smart scale, location home sensor, a smart plug, and a micro-computer, with which they will need to interact with the devices for three months. Specifically, participants should wear the activity tracker wristband (Fitbit Charge 4) 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 will be passively collecting information about their everyday living during these three months. At the end of the 3 month period, the participants will return the devices and will be asked to provide the 5 endpoints and their opinions regarding the usability and acceptability of the platform using structured questionnaires

LifeChamps Platform

Panos D Bamidis, PhD

The LifeChamps Real-Life pilot's objective is to ascertain the feasibility of the use of the LifeChamps solution, previously developed in another clinical trial, in a real-world environment. This solution integrates a health advisory system, and technical intelligence, based on behavioural science, to provide personalized recommendations to follow a healthier lifestyle, to act as a nutrition and physical activity coach, and to guide on social inclusion, among other issues, with the aim of increasing the quality of life. This study is conducted to investigate the feasibility of such an undertaking, assess the clinical impact it may have, as well as evaluate the applicability, usability, and effectiveness of the solution.

"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 pre-post design will be employed, whereby the LifeChamps platform will be deployed for a total of 3 months.

The main research questions of the study are:

1. Is patient recruitment possible in terms of numbers and rates within the recruitment period?
2. Is participant retention in the study possible in terms of numbers and rates?
3. Do participants adhere to the protocol?
4. What are the views/experiences of study participants (patients and healthcare professionals) using the Lifechamps solution (mHealth app and dashboard respectively)?
5. What is the adherence with the usage of the different digital health patients' tools (e.g., usage of mHealth app, smartwatch, smart weight scale)?

Healthcare professionals related to oncology (oncologists, nurses etc.) will also be recruited to use the LifeChamps dashboard and evaluate its usefulness, usability and acceptability. They will have access to and asked to use the LC Dashboard. The LC Dashboard will provide pseudonymised information regarding the patients' physical activity and PROMs for the purpose of the pilot feasibility trial. They will not be able to view real time processed information. After the patients have exited the study, the HCPs will be shown the anonymised outputs of the engine per patient and asked their opinions.

Older patients with a cancer diagnosis will be the target population for this study. Target number of participants is 200. Each study participant will be involved in the study for 3 months in total. A 4-month recruitment period will be allowed, bringing the total study duration to 7 months (from first patient being enrolled until last patient finishing data collection).

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. Study endpoints will be collected at this point.

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.

mHealth 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."

Parallel: Clinical trials with a two arms: A prospective, pre-post design will be employed, whereby the LifeChamps platform will be deployed for a total of 3 months

Real-Life Pilot Feasibility Study (LC_RLP)

LIFECHAMPS: A Collective Intelligence Platform to Support Cancer Champions Real-Life Pilot

Data collected during the Real-Life pilot study, will be made available for sharing via open access repositories, according to the Final Version of the Data Managements Plan of the project.

This outcome will be measured by structured custom made questionnaires, using a 5-level Likert Scale, with 5 representing high acceptance

This outcome will be measured by structured custom made questionnaires, using a 5-level Likert Scale, with 5 representing high usability

This outcome will be calculated by dividing the number of participants consented over the number of approached participants. It is a ratio between 0 and 1, with 1 being the best outcome.

This outcome will be calculated by dividing the number of participants that finished the study over the number of participants that entered the study. It is a ratio between 0 and 1, with 1 being the best outcome.

This outcome will be calculated by dividing the number of times the technology was used over the maximum times that technology can be used over the course of the study. It is a ratio between 0 and 1, with 1 being the best outcome.

This outcome will be measured using the EQ-5D-5L questionnaire. It is using 5-Level Likert scale, with 0 being the best. Also, it includes a self-report of health status using a 0 to 100 scale, 100 being best.

This outcome will be measured using the Functional Assessment of Cancer Therapy - General - 7 Item Version (FACT-G7) Questionnaire. It uses a 5-Level Likert scale, 0 being the best.

This outcome will be measured using the Tilburg Frailty Indicator. It uses Yes-No questions to calculate a score between 0 and 15, with 0 being the best.

This outcome will be measured using the EORTC QUALITY OF LIFE UTILITY - CORE 10 DIMENSIONS (QLU-C10D) Questionnaire. It uses a 4-Level Likert scale, with 4 being the best.

University of Glasgow

Region Stockholm

Hospital Universitario La Fe

Aristotle University Of Thessaloniki

Professor

Nervous System Diseases

Brain Neoplasms

Central Nervous System Neoplasms

Nervous System Neoplasms

Brain Diseases

Central Nervous System Diseases

This cohort will include patients having been diagnosed with a neurological condition.

This cohort will include patients who have not been diagnosed with a neurological disorder.

Amanda Wilburn

Shashaanka Ashili, PhD

Feng Lin, MD PhD

The purpose of this study is to collect clinical data, biological specimens (e.g., blood, tumor, cerebrospinal fluid, urine sample, etc.), and digital health data from patients with tumors, cancer and/or neurological disorders in order to perform research studies that could advance patient care. By collecting these specimens, the investigators plan to create and maintain a biorepository to make data and specimens available to collaborating investigators performing research to discover predictive biomarkers, patterns of care, and personalized treatments that could directly improve the care of our patients through focused proof-of-concept clinical trials.

For brain tumors in particular, this study will provide an important historical dataset against which to compare the addition of novel agents to standard chemoradiation. Despite advancements in surgery, radiotherapy and chemotherapy, the prognosis of malignant gliomas remains poor. Even worse is the prognosis of patients with metastatic brain tumors. However, it is recognized that a small number of brain tumor patients respond durably to specific modalities and treatment regimens and discovery of clinical, imaging, and genetic biomarkers would significantly advance the care of these patients. The development, validation, and application of prognostic biomarkers for primary and secondary brain tumors that predict patient treatment outcome and guide personalized treatment for each patient are of considerable clinical importance. Such prognostic models will allow more informed, pre-treatment decisions about patient response to specific treatments and judiciously guide stratification of patients for specific treatments and enrollment into clinical trials. Prognostic models will also provide a guide and platform for studying many other types of cancer and neurological disorders.

The significance of evaluating the impact of therapy on quality of life and patient-centered outcomes is now widely acknowledged and recognized as one of several measures used to determine clinical benefit. There is increasing evidence that patient reported outcome (PRO) measures are sensitive to changes in disease and treatment characteristics. For example, more recent clinical trials for cancer are now describing the relationship between symptom-based PRO measures and traditional clinical trial endpoints (e.g., overall survival (OS) and progression free survival (PFS)). The relationships between symptoms, signs, and functions are complex, and there is a need to continue to analyze these relationships to determine what is being caused by the treatment and what is being caused by the disease.

Distinguishing outcomes of normal aging from disease is also a challenge, therefore comparing results from patients without neurological disorders ("normal controls") across the spectrum will be an important component of the study.

Samples will be collected leftover from clinical care procedures. These sample types may include: tissue, blood, CSF, fluids, urine, saliva, etc.

Wearable Devices and Biomarkers Project (Healthiomics)

Study of Clinical Biomarkers in Human Health and Disease (Healthiomics)

To collect and store biological specimens (such as, but not limited to, tissue, blood, urine, cerebrospinal fluid, etc.), data from functional and anatomical imaging modalities, digital health data and clinical data from patients with cancer or neurological disorders, those who are under evaluation for a possible cancer or neurologic disorders, or healthy controls.

To perform multi-modality analysis of specimens for biomarker discovery.

To make specimens and data available to collaborating investigators performing IRB-approved research of cancer or neurological disorders.

CureScience

Participants will be provided with the study equipment, i.e., a mobile app, smartwatch, smart scale, location home sensor, a smart plug, and a micro-computer, with which they will need to interact with the devices for three months. Specifically, participants should wear the activity tracker wristband (Fitbit Charge 4) 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 senor (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.

The aim of this study is to facilitate collection of real-world data to test and train the analytics engine for each prototype algorithm. Preliminary datasets will be generated to enable a dry run of the prototype algorithms to check their predictive functionality as part of simulated 'experimental' scenarios at each LifeChamps partner site. This preparatory work will be critical to the development of the LifeChamps platform, prior to progressing to a larger scale feasibility trial.

"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."

Single Group: Clinical trials with a single arm A prospective, time-series design will be employed, whereby the LifeChamps platform will be deployed for a total of 3 months.

Training Data Collection & AI Development

LIFECHAMPS: A Collective Intelligence Platform to Support Cancer Champions Small-Scale Pilot

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 prostate and breast cancer patients across all the data collection process.

Core symptoms/signs of depression and anxiety as measured by PHQ-4 via 0-3 Likert scales, with 3 being the worst.

Initial assessment symptoms palliative care patients' symptoms as measured by ESAS-r via 0-10 Likert scales, with 10 being the worst, and a blank scale for patient-specific symptoms.

Level of adherence to medication as measured by MARS via a Medical adherence Report Scale (MARS) via "yes" or "no" questions attributed with a 0 or 1 point (according to the content of the question), which are then used to calculate a score of adherence.

Function-based risk assessment of health deterioration in older adults as measured by VES-13 via a No Difficulty-Unable to do Likert scale and Yes/No/Don't do questions. All these are attributed to specific points used to calculate the final score. Scoring ranges between 0 and 10, 10 being the worse outcome.

Quality of life assessment as measured by LASA via 0-10 Likert scales, with 10 being the best.

Cognitive and emotional representations of illness as measured by Brief Illness Perception Questionnaire via eight 0-10 Likert scaled questions and one open ended. The questionnaire does not have a best or worst outcome, rather it attempts to ascertain the patient's perception of the illness.

Tracking symptoms of prostate cancer as measured by International Prostate Symptom Score (IPSS) via 0-5 Likert scales, with 5 signifying higher frequency of symptoms.

Assessment of erectile/sexual function as measured by International Index Erectile Function-6 via 0-5 Likert scales, with 5, being the best outcome

Part of International Prostate Symptom Score measured by a 0-6 Likert scale with 6 being the worst.

Behaviors and Mental Disorders

Rare Diseases

Melanoma

Neuroendocrine Tumors

Neuroectodermal Tumors

Neuroectodermal Tumors, Primitive

Neoplasms, Germ Cell and Embryonal

Neoplasms by Histologic Type

Neoplasms, Nerve Tissue

Nevus, Pigmented

Nevus

Nevi and Melanomas

Skin Neoplasms

Skin Diseases

Quality of Life

Neuroendocrine Tumor

Neuroepithelioma

Participants will be asked to use the LifeChamps platform and will be provided with the study equipment (sensors/home kit).

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.

Panagiotis Papachristou, MD/PhD

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

"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."

LifeChamps Feasibility Study

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

According to GDPR and the Swedish Ethical Review Authority, data may be made available to those who comply with necessary ethical approvals and regulations for the planned data

Study recruitment rates, participant retention and adherence to study protocol will be calculated.

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.

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.

PROM assesment of the FCRI Short Form 9-item questionnaire (Simard, S; Savard, J; 2015)

Assessment as measured by SEPI via 0-4 point Likert scales.

Symptoms and General Pathology

Mobility Limitation

Technology allowing measurement of physical activity

Activity monitor

Richard M Kwasnicki, PhD MRCS

Daniel R Leff, PhD FRCS

Richard Kwasnicki

This work aims to use wearable sensors to record the return towards normal physical activity after breast surgery. It will build on current evidence by using objective measures of activity and arm movements rather than patient reports.

Breast: Recovery After Axillary Node Clearance - Evaluating Limbs With E-Technology (the BRACELET Study)

Arm movements as measured by wearable sensor

Imperial College London

Respiratory Tract (Lung and Bronchial) Diseases

Digestive System Diseases

Gland and Hormone Related Diseases

Lung Neoplasms

Stomach Neoplasms

Ovarian Neoplasms

Carcinoma, Ovarian Epithelial

Stomach Cancer

Ovarian Cancer

Ovarian Epithelial Cancer

In addition to standard of care services at the participant's respective health system, and study specific collection of clinical, PRO, and wearable data, as well as microbiome specimens, individuals randomized to the intervention group will receive immediate enrollment to a 6-month digital health coaching program followed by 6 months monitoring via PRO, wearable, and clinical data collection. They will collect fecal microbiome samples at baseline (study enrollment) and month 6 following enrollment.

In addition to standard of care services, individuals in the wait list control will be monitored via the collection of PRO, clinical, and wearable data for the first 6 months, along with fecal microbiome collection at study enrollment baseline (study enrollment) and month 6. At month 6 these individuals will be enrolled into the 6-month digital health coaching program, during which clinical, PRO and wearable data will continue to be collected. At the completion of the 6-month coaching these individuals will come off study and will not receive additional follow-up.

A cohort of consisting of adults without a cancer diagnosis residing in the same residence as participants, will be consented to collect fecal microbiome specimens to serve as a control for potential regional variation in microbiome dysbiosis. Up to 25 healthy controls will be enrolled per 100 participants at each study site. At sites enrolling fewer than 100 participants, an n up to 25% of the total patient enrollment sample will be approached for enrollment.

Coaching consisting of weekly calls and delivery of evidence-based content across health and wellness domains (e.g. nutrition, exercise, physical, emotional and financial health) up to 4 times weekly via text, email or mobile application.

Digital Health Coaching Program

Device: Fitbit A wrist-worn activity tracker allowing for the capture of physical activity, including but not limited to step-count and minutes of activity, to be captured daily.

Fitbit

Kelly J Brassil, PhD

Jennifer Loftis, DNP

Angela R Starkweather, PhD, FAAN

Debra L Lynch Kelly, PhD, FAAN

Marilyn Hammer, PhD

Alexi Wright, MD, MPH

Rachael Schmidt, DNP

Robin M Lally, PhD

Kristen L Fessele, PhD

Laura Flora, BA

Elizabeth Arthur, PhD

Jessica L Krok-Schoen, PhD

Meagan Whisenant, Phd

Darcy Ponce, BS

Meagan Whisenant, PhD

Debu Tripathy, MD

Abbey Kaler, MSN

Kaukab I Jafry, MD, MBBS

Martha Thompson

Anneliese Gonzalez, MD

Alexi Wright, MD

Jessica Krok-Schoen, PhD

Robin Lally, PhD

Angela Starkweather, PhD

Debra Lynch-Kelly, PhD

Kristen Fessele, PhD

This study intends to explore feasibility, acceptability, and outcomes related to the use of a digital health coaching intervention for individuals who have completed primary therapy for cancer. Up to 500 individuals with diverse cancer diagnoses will be enrolled across up to 5 clinical sites to participate in a randomized wait-list control study. Those in the intervention group will receive 6 months of digital coaching up front followed by 6 months of ongoing monitoring via patient reported and clinical outcomes, as well as wearable data. Those in the control group will be monitored via patient reported and clinical outcomes as well as wearable data for the first 6 months followed by 6 months of digital health coaching. Both groups will collect fecal microbiome samples at enrollment and month 6. The study aims to explore if and how digital health coaching may be used to enhance outcomes for individuals following completion of primary cancer therapy.

Background: There are an estimated 16.9 million cancer survivors in the United States, accounting for approximately 5% of the entire US population, and this number is anticipated to increase by 31% over the next 10 years to include 22.2 million individuals.1 Due to advances in therapy individuals with cancer are experiencing increased overall survival that is often accompanied by the management of cancer as a chronic condition.2 As such many individuals require maintenance therapies that extend for months or years beyond the completion of primary therapy with surgery, radiation, and/or pharmacologic therapies. Chronic management of cancer care may include both long-term maintenance therapy as well as the management of treatment-related sequelae, the majority of which occurs beyond the clinical setting. Supportive care needs include symptom support, general wellness, and a focus on the importance of adherence to treatment and follow-up, all of which may influence quality and quantity of life. Accordingly, there is a critical and growing need for comprehensive, accessible platforms to support survivor self-management of symptoms and general wellness (including physical, functional, and psychosocial well-being and healthcare adherence). There is furthermore a critical knowledge gap on the correlation between individual symptoms and wellness on novel biomarkers, specifically intestinal (gut) microbiome. Gut microbiome regulates critical physiological processes-digestion, mood, and overall immune health, but to date studies have focused on dysbiosis during cancer treatment. The investigators seek to explore dynamics of gut microbiota after cancer treatment and understand how health behavioral changes prompted by health coaching to modulate symptoms and physical/ psychosocial well-being may also positively influence the restoration of gut flora.

Aims: The objective of this randomized, wait-list control study is to assess the effect of a 6-month digital health coaching program in cancer survivors within 1 year of primary treatment and longitudinally measure its impact on multifaceted health outcomes. The investigators aim to: 1) Primarily, assess the feasibility, acceptability, and effect of digital health coaching on participants' health self-efficacy; 2) Secondarily, characterize associations between participant symptoms, physical/psychosocial well-being, and health self-management and gut microbiota changes; and 3) Explore patient-generated health data outcomes among participants (patient-reported \[PROs\] and wearable biometrics outcomes).

Methods: The proposed study will utilize a randomized-wait list control design to enroll up to1500 individuals with diverse tumor types who have completed primary treatment and are within 1 year of diagnosis. Each of up to 15 collaborating sites will enroll 100 participants. Participants will be enrolled in a 6-month digital health coaching program that combines person-to-person calls once weekly, accompanied by up to 4 digital nudges of evidence-based content via text, email and/or mobile application, based on the participant's preference. Content will focus on key topics designed to optimize survivorship outcomes, including management of late and long-term effects of therapy, diet and exercise, fatigue, financial toxicity, and other associated symptoms (e.g., sleep disturbance, depression), medication adherence, surveillance, and managing anxiety and fear of cancer recurrence. The program emphasizes targeting modifiable behaviors that can improve quality of life and health outcomes, including progression-free and overall survival. Those randomized to the intervention group will receive the 6-month coaching intervention up front followed by 6 months of on-going clinical, patient reported, activity, and microbiome data collection. Those randomized to the control will receive 6-months of clinical, patient reported, activity, and microbiome data collection, after which they will be randomized to the digital health coaching intervention.

Outcome Measures: All participants will be followed for 12-months during which time they will be provided with Fitbit devices to track engagement in physical activity. Microbiome samples will be collected at enrollment and 6 months to explore biomarkers of inflammation, which will be analyzed to examine associations between microbiota signatures and engagement in physical activity and PROs. Genomic bacterial DNA will be extracted and analyzed for any taxonomic changes in the microbiota diversity and composition with 16s rRNA sequencing. Microbiome analysis will be conducted in partnership with The National Institute of Nursing Research (NINR). PROs will be collected at baseline and months 3, 6, 9, and 12 to track progress during and following the program and to provide insights into the experience of quality of life, symptom burden, mental health, cognitive function, sleep quality, sexual health, and financial toxicity.

Rationale: This program seeks to address survivors' total well-being, including co-morbid conditions, psychosocial wellness, and healthy lifestyle behaviors, to enhance outcomes for individuals who have completed primary therapy for a cancer diagnosis. The approach is innovative in exploring how digital health coaching may be used to support the holistic needs of cancer survivors beyond the clinical care setting. The robust collection of patient-reported, wearable, biomarker, and clinical data, as well as qualitative data related to patient priorities, concerns and challenges in the context of Health Coaching, will allow for triangulation of data to comprehensively inform the experience of individuals following primary therapy as they manage their health in the community setting.

Wait list control trial in which 100 patients will be randomized to receive either 6-months of digital coaching immediately followed by 6-months of monitoring or 6-months of monitoring followed by 6-months of digital health coaching. All participants will receive 12 months of patient reported outcomes collection and activity tracking via wrist-worn devices, as well as microbiome collection at baseline and month 6 only.

Comprehensive Outcomes for After Cancer Health

Comprehensive Outcomes for After Cancer Health (COACH): The Feasibility and Impact of an mHealth Augmented Coaching Program for Self-Management in Cancer Survivors

An electronic food diary assessment capturing dietary intake over the last 24 hours. The number of items

A three-item instrument used to measure medication adherence, asking about difficulty taking medications on time, average days per week with one dose missed, and the last time a dose was missed. Responses are on differing scales, with higher values meaning better adherence.

Step count will be collected via Fitbits provided to study participants

Minutes of physical activity will be collected via Fitbits provided to study participants

Frequency, types and duration of engagement with the digital health coaching platform

16s analysis of fecal microbiome specimens self-collected by participants

ER visits and unplanned hospitalizations as documented in the electronic health record

A 3-item questionnaire evaluating the following: 1) The digital health coaching program is easy to participate in; 2) the digital health coaching program is useful to me; 3) the digital health coaching program is relevant to my survivorship experience. Responses will be provided on a 10-point Likert scale ranging from 1 (Not at all) to 10 (Very Much).

A retention rate greater than or equal to 70%. Retention is defined as individuals who agree to participate in the digital health coaching program completing the 6-months of engagement post-enrollment.

A 6-item instrument measures how confident an individual is in engaging in certain health management activities. Responses are provided on a 10-point scale ranging from 1(not at all confident) to 10 (totally confident). A mean score is calculated for the instrument with a higher score indicating higher self-efficacy.

A 12-item instrument assessing respondents' abilities to perform physical tasks and activities of daily living. Items are scored on 5-point Likert scales, with higher scores indicating higher physical functioning.

A 27-item instrument using a 5-point Likert scale ranging from 0 (not at all) to 4 (very much) to measure QoL across four dimensions: physical, social/family, emotional and functional. The FACT-G, validated for use with individuals with diverse cancer types, in addition to condition specific items as available by tumor type.

An 8-item instrument measuring indicators of anxiety with a recall period over the last 7 days. Responses are provided on a 5-point scale ranging from 1(never) to 5 (always). A summed score is calculated for the instrument with a higher score indicating greater anxiety.

An 8-item instrument measuring indicators of depression with a recall period over the last 7 days. Responses are provided on a 5-point scale ranging from 1(never) to 5 (always). A summed score is calculated for the instrument with a higher score indicating greater depression.

An 8-item instrument measuring indicators of cognitive function with a recall period over the last 7 days. Responses are provided on a 5-point scale ranging from 1(never) to 5 (always). A summed score is calculated for the instrument with a higher score indicating greater cognitive impairment.

An 8-item instrument measuring indicators of sleep-related impairment with a recall period over the last 7 days. Responses are provided on a 5-point scale ranging from 1(never) to 5 (always). A summed score is calculated for the instrument with a higher score indicating greater sleep-related impairment.

An 11-item instrument measuring indicators of male sexual function and satisfaction with a recall period over the last 30 days. Responses are provided on various 2- to 10-point scales across 10 domains: interest in sexual activity, orgasm ability, orgasm satisfaction, oral discomfort, oral dryness, satisfaction with sex life, erectile function. For each item on the instrument a higher score indicates more of the concept being described.

A 14-item instrument measuring sexual function and satisfaction for women with a recall period over the last 30 days. Responses are provided on various 2- to 10-point scales across 7 domains: interest in sexual activity, lubrication for sexual activity, orgasm ability, orgasm pleasure, oral discomfort, oral dryness, satisfaction with sex life, vaginal discomfort, vulvar discomfort-clitoral, vulvar discomfort-labial. For each item on the instrument a higher score indicates more of the concept being described.

An 11-item instrument measuring the financial toxicity of cancer treatment utilizing a five-point ordinal scale ranging from (0- Not at all) to (4- Very much).

An 16-item instrument measuring the financial toxicity of cancer treatment. The first 15 items are rated on an 11-point scale ranging from 0 (lowest financial toxicity burden) to 10 (most severe financial toxicity burden). A final item asks individuals to rank their overall financial situation at the time of the survey compared to prior to their cancer diagnosis, using a 5-point response ranging from much better to much worse.

A 10-item instrument measuring the presence of commonly observed symptoms in individuals with a cancer diagnosis (9 specific items and 1 allowing entry of other problems). Responses for a recall period of the last 24 hours are recorded on an 11-point scale ranging from 0 (none/not present) to 10 (worst possible).

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Real-Life Pilot Feasibility Study (LC_RLP)	NCT05797727	Breast Cancer Prostate Cancer	LifeChamps Plat... LifeChamps Plat...	65 Years -	Aristotle University Of Thessaloniki
Wearable Devices and Biomarkers Project (Healthiomics)	NCT05106725	Brain Cancer Neurological Di... Neurological Ca...		18 Years -	CureScience
Training Data Collection & AI Development	NCT05378854	Breast Cancer Prostate Cancer	LifeChamps Plat...	65 Years -	Aristotle University Of Thessaloniki
LifeChamps Feasibility Study	NCT05990634	Melanoma (Skin)	LifeChamps Plat...	65 Years -	Region Stockholm
Breast: Recovery After Axillary Node Clearance - Evaluating Limbs With E-Technology (the BRACELET Study)	NCT03635723	Breast Cancer Mobility Limita...	Activity monito...	-	Imperial College London
Training Data Collection & AI Development	NCT05378854	Breast Cancer Prostate Cancer	LifeChamps Plat...	65 Years -	Aristotle University Of Thessaloniki
Wearable Devices and Biomarkers Project (Healthiomics)	NCT05106725	Brain Cancer Neurological Di... Neurological Ca...		18 Years -	CureScience
Breast: Recovery After Axillary Node Clearance - Evaluating Limbs With E-Technology (the BRACELET Study)	NCT03635723	Breast Cancer Mobility Limita...	Activity monito...	-	Imperial College London
Comprehensive Outcomes for After Cancer Health	NCT05349227	Ovarian Cancer Breast Cancer Lung Cancer Gastric Cancer Survivorship	Digital Health ... Fitbit	18 Years -	Pack Health

Spots Global Cancer Trial Database for wearables

Every month we try and update this database with for wearables cancer trials from around the world to help patients and their families find trials that might be right for them.
We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.

Spots Global Cancer Trial Database for wearables

Every month we try and update this database with for wearables cancer trials from around the world to help patients and their families find trials that might be right for them. We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.

Every month we try and update this database with for wearables cancer trials from around the world to help patients and their families find trials that might be right for them.
We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.