xml: <clinical_study>
    <!-- This xml conforms to an XML Schema at:
      https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
    <required_header>
      <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
      <link_text>Link to the current ClinicalTrials.gov record.</link_text>
      <url>https://clinicaltrials.gov/ct2/show/NCT05990634</url>
    </required_header>
    <id_info>
      <org_study_id>X00568</org_study_id>
      <secondary_id>GA875329</secondary_id>
      <nct_id>NCT05990634</nct_id>
    </id_info>
    <brief_title>LifeChamps Feasibility Study</brief_title>
    <official_title>LIFECHAMPS: A Collective Intelligence Platform to Support Cancer Champions - Stockholm Pilot Use Case 2</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Region Stockholm</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>Aristotle University Of Thessaloniki</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>Hospital Universitario La Fe</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>University of Glasgow</agency>
        <agency_class>Other</agency_class>
      </collaborator>
    </sponsors>
    <source>Region Stockholm</source>
    <oversight_info>
      <has_dmc>No</has_dmc>
      <is_fda_regulated_drug>No</is_fda_regulated_drug>
      <is_fda_regulated_device>No</is_fda_regulated_device>
    </oversight_info>
    <brief_summary>
      <textblock>
        The purpose of this study is to collect data from various sources (PROM / PREM, sensors,&#xD;
        journal data) to train AI based models in the LifeChamps digital platform in a pre-pilot, as&#xD;
        well as partly implement a pilot/feasibility study to examine the applicability of the&#xD;
        digital technology developed in LifeChamps, as well as the usability for patients (cancer&#xD;
        survivors) and health care professionals&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        &quot;The LifeChamps project (https://lifechamps.eu/) is creating a digital platform to support&#xD;
        clinical teams to provide more integrated follow-up care to older patients with cancer. The&#xD;
        digital platform will integrate data coming directly from the patient (patient-reported&#xD;
        outcomes and sensor data from wearable devices), from the home environment (home sensors,&#xD;
        weight scales), and from the clinical environment (data routinely collected via the&#xD;
        Electronic Health Record). The digital platform will use big data analytics (machine&#xD;
        learning) to process all data as part of predictive clinical algorithms for frailty and&#xD;
        quality of life for older patients with cancer. Development of each clinical algorithm&#xD;
        requires that the prototype model (or analytics engine) is trained using abundant real-world&#xD;
        data to help consolidate the predictive ability and validity of the algorithms before the&#xD;
        algorithms are deployed in the feasibility trial.&#xD;
  &#xD;
        A prospective, time series design will be employed, whereby the LifeChamps platform will be&#xD;
        deployed first during the pre-pilot in a total of 3 months; later in an interrupted time&#xD;
        series feasibility trial during a period of 5 months.&#xD;
  &#xD;
        Older patients with a cancer diagnosis (specifically melanoma) will be the target population&#xD;
        for this study. Consecutive sampling will be used, whereby all older patients with cancer who&#xD;
        meet the eligibility criteria will be approached and invited in the study. Each study&#xD;
        participant will be involved in the study for 3 months or 5 months in total respectively. A&#xD;
        3-month recruitment period will be allowed and is overlapping with the two studies, bringing&#xD;
        the total study duration to 6 months (from first patient being enrolled until last patient&#xD;
        finishing data collection).&#xD;
  &#xD;
        Patients aged 65 years and above, diagnosed with stage I-III melanoma skin cancer will be&#xD;
        identified from Region Stockholm participating primary care facilities and the Melanoma&#xD;
        patient association (Melanomföreningen) . The patients will be presented with the opportunity&#xD;
        to participate in the study and screened based on the inclusion and exclusion criteria.&#xD;
        Potential participants will be provided with the information sheet and the consent form,&#xD;
        informed that should they decline to participate this will not change their current treatment&#xD;
        and provided the opportunity to ask any questions they may have.&#xD;
  &#xD;
        After written informed consent has been provided, the mini-COG will be used to evaluate study&#xD;
        participants' cognitive function and impairment at baseline. The mini-COG consists of a&#xD;
        3-word recall and a clock-drawing test, and can be completed within 5 minutes. A score of&#xD;
        less than 3/5 indicates the need to refer the patient for full cognitive assessment.&#xD;
  &#xD;
        The researcher will also arrange for study participants to receive study equipment, i.e. home&#xD;
        sensors, wearable activity sensors, smart weight scale, and mobile app. The researcher will&#xD;
        arrange a suitable time for a home visit to install the home sensors and test functionality.&#xD;
        The researcher will demonstrate use of study equipment to the participant, and reiterate that&#xD;
        support with use of the technology will be available.&#xD;
  &#xD;
        Data collection will involve a variety of sources, including the patient (patient-reported&#xD;
        outcomes and sensor data from wearable devices), the home environment (home sensors, weight&#xD;
        scales), and the clinical site (data routinely collected via the Electronic Health Record).&#xD;
  &#xD;
        The following technology will be used:&#xD;
  &#xD;
        Mobile devices:&#xD;
  &#xD;
        Activity tracker wristband (FitBit charge 4). It will be used to passively monitor and&#xD;
        collect data on heart rate, heart rate variability, steps, activity tracking, sleep&#xD;
        monitoring, breathing rate, skin temperature and SpO2.&#xD;
  &#xD;
        Smart T-shirt (Move Sense). It will be used to track participants heart rate (HR),&#xD;
        respiration and movement (body position).&#xD;
  &#xD;
        Mobile app (SALUMEDIA). It will be used to enable collection of patient-reported outcome&#xD;
        measures (PROMs) and to forward this information along with the data gathered by the activity&#xD;
        tracker and the smart scale to the Raspberry Pi Kit at home.&#xD;
  &#xD;
        At home sensors / devices:&#xD;
  &#xD;
        LOCS Home sensors: They will be used to monitor participants' daily activities e.g., to track&#xD;
        ambulation and functioning. Study participants will be provided with 4 motion sensors, 1 door&#xD;
        contact sensor, 2 corridor sensors, and a tag device.&#xD;
  &#xD;
        Smart Scale (Withings Body+): It will be used to measure weekly body weight, body composition&#xD;
        and body mass index.&#xD;
  &#xD;
        Raspberry Pi (RPI) kit: As an edge gateway, RPI is hosting LOCS gateway, Movesense Gateway&#xD;
        and data ingestion service. RPI will enable data collection and edge analytics and transfer&#xD;
        of data to the LIFECHAMPS platform.&#xD;
  &#xD;
        Selected study participant clinical and demographic data from the local EHRs will be&#xD;
        collected and loaded onto the LifeChamps analytics engine. The data will be loaded by&#xD;
        technical partners via the LifeChamps dashboard for processing and analysis. Data regarding&#xD;
        recruitment rate (patients consenting / patients approached), participant retention in the&#xD;
        study, reasons for study discontinuation (if offered), participant adherence with technology,&#xD;
        issues with technology and need for troubleshooting will be recorded. These data will (a) be&#xD;
        recorded by local researchers using bespoke 'recording logs' in the form of an Excel&#xD;
        spreadsheet, and (b) remotely monitored and logged by technical partners involved in the&#xD;
        distribution / management of the technology to be used in the trial as described above.&quot;&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Active, not recruiting</overall_status>
    <start_date type="Actual">March 1, 2023</start_date>
    <completion_date type="Anticipated">November 2023</completion_date>
    <primary_completion_date type="Anticipated">September 2023</primary_completion_date>
    <phase>N/A</phase>
    <study_type>Interventional</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <allocation>N/A</allocation>
      <intervention_model>Single Group Assignment</intervention_model>
      <primary_purpose>Supportive Care</primary_purpose>
      <masking>None (Open Label)</masking>
    </study_design_info>
    <primary_outcome>
      <measure>Analytical models</measure>
      <time_frame>3 to 6 Months</time_frame>
      <description>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.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Usability assessment</measure>
      <time_frame>3 to 6 Months</time_frame>
      <description>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.</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>QoL assessment</measure>
      <time_frame>3 to 6 Months</time_frame>
      <description>Quality of life assessment as measured by LASA via 0-10 Likert scales, with 10 being the best.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Fear of Cancer Recurrency (FCRI)</measure>
      <time_frame>3 to 6 Months</time_frame>
      <description>PROM assesment of the FCRI Short Form 9-item questionnaire (Simard, S; Savard, J; 2015)</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Sun Exposure and Protection Index (SEPI)</measure>
      <time_frame>3 to 6 Months</time_frame>
      <description>Assessment as measured by SEPI via 0-4 point Likert scales.</description>
    </secondary_outcome>
    <other_outcome>
      <measure>Retention and adherence to study protocol</measure>
      <time_frame>9 to 12 Months</time_frame>
      <description>Study recruitment rates, participant retention and adherence to study protocol will be calculated.</description>
    </other_outcome>
    <other_outcome>
      <measure>Technology adherence</measure>
      <time_frame>3 to 6 Months</time_frame>
      <description>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.</description>
    </other_outcome>
    <number_of_arms>1</number_of_arms>
    <enrollment type="Actual">20</enrollment>
    <condition>Melanoma (Skin)</condition>
    <arm_group>
      <arm_group_label>LifeChamps Platform</arm_group_label>
      <arm_group_type>Experimental</arm_group_type>
      <description>Participants will be asked to use the LifeChamps platform and will be provided with the study equipment (sensors/home kit).</description>
    </arm_group>
    <intervention>
      <intervention_type>Device</intervention_type>
      <intervention_name>LifeChamps Platform</intervention_name>
      <description>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.</description>
      <arm_group_label>LifeChamps Platform</arm_group_label>
    </intervention>
    <eligibility>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Diagnosed with malignant melanoma (stage I-III) and undergone primary treatment within&#xD;
               the last 36 months.&#xD;
  &#xD;
            -  Has completed primary and secondary cancer treatment and is now in remission&#xD;
               (survivorship stage).&#xD;
  &#xD;
            -  Assessed as physically and mentally able to participate in the study&#xD;
  &#xD;
            -  Can read, write and understand the Swedish language&#xD;
  &#xD;
            -  Can bring and use their own smart phone (Android version 10 or newer) below the study&#xD;
  &#xD;
            -  Have 24-hour access to internet (broadband) via WiFi router in your own household&#xD;
               and/or free 4G mobile data (sim card and 4G router will be provided if this criterion&#xD;
               is not met)&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  Terminal cancer stage or prognosis &lt;18 months from time of recruitment&#xD;
  &#xD;
            -  Diagnosed with severe mental illness or cognitive illness that affects the ability to&#xD;
               participate&#xD;
  &#xD;
            -  Screening with Mini-Cog where the result is between 0-2&#xD;
  &#xD;
            -  Inability or unwillingness to provide written informed consent&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>65 Years</minimum_age>
      <maximum_age>N/A</maximum_age>
      <healthy_volunteers>No</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Panagiotis Papachristou, MD/PhD</last_name>
      <role>Principal Investigator</role>
      <affiliation>Region Stockholm, Academic Primary Health Care Centre</affiliation>
    </overall_official>
    <location>
      <facility>
        <name>Academic Primary Health Care Centre</name>
        <address>
          <city>Stockholm</city>
          <zip>11863</zip>
          <country>Sweden</country>
        </address>
      </facility>
    </location>
    <location_countries>
      <country>Sweden</country>
    </location_countries>
    <link>
      <url>http://lifechamps.eu</url>
      <description>Project website</description>
    </link>
    <verification_date>August 2023</verification_date>
    <study_first_submitted>June 7, 2022</study_first_submitted>
    <study_first_submitted_qc>August 6, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 14, 2023</study_first_posted>
    <last_update_submitted>August 6, 2023</last_update_submitted>
    <last_update_submitted_qc>August 6, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 14, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <keyword>Melanoma</keyword>
    <keyword>Cancer</keyword>
    <keyword>Survivorship</keyword>
    <keyword>Quality of Life</keyword>
    <keyword>mHealth application</keyword>
    <keyword>Wearables</keyword>
    <keyword>Artificial Intelligence</keyword>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Melanoma</mesh_term>
    </condition_browse>
    <patient_data>
      <sharing_ipd>No</sharing_ipd>
      <ipd_description>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</ipd_description>
    </patient_data>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: download date: ClinicalTrials.gov processed this data on September 20, 2023
  link text: Link to the current ClinicalTrials.gov record.
  url: https://clinicaltrials.gov/ct2/show/NCT05990634
  org study id: X00568
  secondary id: GA875329
  nct id: NCT05990634
  lead sponsor: 
  collaborator: 
  collaborator: 
  collaborator: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  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."
  allocation: N/A
  intervention model: Single Group Assignment
  primary purpose: Supportive Care
  masking: None (Open Label)
  measure: Analytical models
  time frame: 3 to 6 Months
  description: 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.
  measure: Usability assessment
  time frame: 3 to 6 Months
  description: 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.
  measure: QoL assessment
  time frame: 3 to 6 Months
  description: Quality of life assessment as measured by LASA via 0-10 Likert scales, with 10 being the best.
  measure: Fear of Cancer Recurrency (FCRI)
  time frame: 3 to 6 Months
  description: PROM assesment of the FCRI Short Form 9-item questionnaire (Simard, S; Savard, J; 2015)
  measure: Sun Exposure and Protection Index (SEPI)
  time frame: 3 to 6 Months
  description: Assessment as measured by SEPI via 0-4 point Likert scales.
  measure: Retention and adherence to study protocol
  time frame: 9 to 12 Months
  description: Study recruitment rates, participant retention and adherence to study protocol will be calculated.
  measure: Technology adherence
  time frame: 3 to 6 Months
  description: 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.
  arm group label: LifeChamps Platform
  arm group type: Experimental
  description: Participants will be asked to use the LifeChamps platform and will be provided with the study equipment (sensors/home kit).
  intervention type: Device
  intervention name: LifeChamps Platform
  description: 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.
  arm group label: LifeChamps Platform
  criteria: 
  gender: All
  minimum age: 65 Years
  maximum age: N/A
  healthy volunteers: No
  last name: Panagiotis Papachristou, MD/PhD
  role: Principal Investigator
  affiliation: Region Stockholm, Academic Primary Health Care Centre
  facility: 
  country: Sweden
  url: http://lifechamps.eu
  description: Project website
  responsible party type: Sponsor
  mesh term: Melanoma
  sharing ipd: No
  ipd description: 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