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/NCT05971277</url>
    </required_header>
    <id_info>
      <org_study_id>150745</org_study_id>
      <secondary_id>312296</secondary_id>
      <nct_id>NCT05971277</nct_id>
    </id_info>
    <brief_title>Home And Locally Observed - Tracking (HALO-Trak)</brief_title>
    <acronym>HALO-Trak</acronym>
    <official_title>Proof of Concept (POC) Prospective Observational Study to Test a Framework for Integration of Data Streams, Including Molecular Genomic Markers and Wearable Device Data in Patients Receiving Chemotherapy for Advanced Cancer</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>University College, London</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
    </sponsors>
    <source>University College, London</source>
    <oversight_info>
      <is_fda_regulated_drug>No</is_fda_regulated_drug>
    </oversight_info>
    <brief_summary>
      <textblock>
        The goal of this observational study is to collect biometric, HRQoL, immune response and&#xD;
        genomic data continuously and intermittently during and after chemo or immunotherapy for the&#xD;
        generation of a complex dataset using a platform which can aggregate different types of data&#xD;
        collected over a time period and, to test the potential for analysis within and across data&#xD;
        sets with linkage to clinical outcomes. The framework will have capabilities to integrate&#xD;
        data from electronic medical records (EMRs) such as Epic, as well as digital streams&#xD;
        including sensor, genomic, imaging and pathology. Such a platform can realise the potential&#xD;
        for machine learning (ML) methodologies to address important cancer outcomes.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        The Investigators overarching aim is to determine the relationship between measures of&#xD;
        physical performance status including heart rate and steps, health related quality of life&#xD;
        (HRQoL) and genomic and immunogenomic phenotype on cancer outcomes in patients receiving&#xD;
        chemotherapy or immunotherapy for haematological or metastatic cancer including renal&#xD;
        (papillary, and RCC), breast, prostate, and other solid tumours. The primary objective is to&#xD;
        test the feasibility of integrating diverse data streams (genomic, HR QoL and biometric) on a&#xD;
        novel platform, capable of integrating data streams thus generating complex datasets for&#xD;
        analyses using machine learning methodologies.&#xD;
  &#xD;
        Secondary objectives will be to conduct exploratory analysis assessing the relationship&#xD;
        between individual and combined data types and cancer outcomes.&#xD;
  &#xD;
        Analysis using existing and novel computational models will be applied to the data to events&#xD;
        in the acute and chronic setting that are common in patients diagnosed with cancer undergoing&#xD;
        systemic therapy such as chemotherapy and immunotherapy. The outputs from this study will&#xD;
        help inform future studies and trials designed to inform patients about their health status&#xD;
        during cancer therapy&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Recruiting</overall_status>
    <start_date type="Actual">January 30, 2023</start_date>
    <completion_date type="Anticipated">April 1, 2026</completion_date>
    <primary_completion_date type="Anticipated">April 1, 2025</primary_completion_date>
    <study_type>Observational</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <observational_model>Cohort</observational_model>
      <time_perspective>Prospective</time_perspective>
    </study_design_info>
    <primary_outcome>
      <measure>Primary Objective</measure>
      <time_frame>one month to 52 weeks</time_frame>
      <description>To measure feasibility of data collection longitudinally in a patient cohort undergoing systemic therapy for metastatic or haematological cancer.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Remote monitoring data</measure>
      <time_frame>one month to 52 weeks</time_frame>
      <description>To collect activity (steps) and heart rate data. This will be collected using the Ethera Wellness app which participants will download onto their smartphone devices.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Biological sample data. This will include blood samples (30mls) maximum frequency will be monthly</measure>
      <time_frame>one month to 52 weeks</time_frame>
      <description>This will include blood samples (30mls) and stool samples maximum frequency will be monthly</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Clinical Outcome data</measure>
      <time_frame>one month to 52 weeks</time_frame>
      <description>Data will be collected via an electronic case report form-</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Quality of life Questionnaire</measure>
      <time_frame>one month to 52 weeks</time_frame>
      <description>EORTC QLQ C30- questionnaire will be collected monthly</description>
    </primary_outcome>
    <enrollment type="Anticipated">200</enrollment>
    <condition>Advanced Cancer</condition>
    <intervention>
      <intervention_type>Device</intervention_type>
      <intervention_name>Halo Wearable data device</intervention_name>
      <description>A wrist-worn tracker with heart-rate monitor and pedometer (step counter), as well as a mobile app.</description>
    </intervention>
    <biospec_retention>Samples With DNA</biospec_retention>
    <biospec_descr>
      <textblock>
        Genomic and microbiome analysis, statistical analysis&#xD;
      </textblock>
    </biospec_descr>
    <eligibility>
      <study_pop>
        <textblock>
          All patients will be receiving standard of care therapies and will be recruited from&#xD;
          Oncology clinics once a diagnosis of metastatic or haematological cancers has been&#xD;
          established and patients meet all the inclusion criteria&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  ● A diagnosis of a metastatic or haematological cancer undergoing systemic therapy&#xD;
  &#xD;
                 -  Undergoing at least 1 planned cycle of chemotherapy or immunotherapy, according&#xD;
                    to standard of care practices.&#xD;
  &#xD;
                 -  Ability to understand and the willingness to sign a written informed consent.&#xD;
  &#xD;
                 -  Able to ambulate without assistance or walking aid.&#xD;
  &#xD;
                 -  Have an Android or iOS phone and willing to download the Ethera app&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  ● Physical disabilities that preclude daily walking&#xD;
  &#xD;
                 -  Inability to provide informed consent.&#xD;
  &#xD;
                 -  Unable to use and operate the Ethera Health Monitoring Smartphone App. (Apple or&#xD;
                    Android)&#xD;
  &#xD;
                 -  Medical or psychiatric condition which in the investigator's opinion would affect&#xD;
                    the successful completion of the study.&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>18 Years</minimum_age>
      <maximum_age>N/A</maximum_age>
      <healthy_volunteers>No</healthy_volunteers>
    </eligibility>
    <overall_contact>
      <last_name>John D Kelly, Professor</last_name>
      <phone>07549152902</phone>
      <email>j.d.kelly@ucl.ac.uk</email>
    </overall_contact>
    <overall_contact_backup>
      <last_name>Hazel McBain</last_name>
      <phone>07342976009</phone>
      <email>hazelmcbain@nhs.net</email>
    </overall_contact_backup>
    <location>
      <facility>
        <name>UCL London</name>
        <address>
          <city>London</city>
          <zip>W1W 7TY</zip>
          <country>United Kingdom</country>
        </address>
      </facility>
      <status>Recruiting</status>
      <contact>
        <last_name>John D Kelly, Professor</last_name>
        <phone>075497152902</phone>
        <email>j.d.kelly@ucl.ac.uk</email>
      </contact>
      <contact_backup>
        <last_name>Hazel McBain, Snr Nurse</last_name>
        <phone>07342976009</phone>
        <email>hazelmcbain@nhs.net</email>
      </contact_backup>
    </location>
    <location_countries>
      <country>United Kingdom</country>
    </location_countries>
    <verification_date>January 2023</verification_date>
    <study_first_submitted>January 9, 2023</study_first_submitted>
    <study_first_submitted_qc>July 24, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 2, 2023</study_first_posted>
    <last_update_submitted>July 24, 2023</last_update_submitted>
    <last_update_submitted_qc>July 24, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 2, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Neoplasms</mesh_term>
    </condition_browse>
    <!-- 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/NCT05971277
  org study id: 150745
  secondary id: 312296
  nct id: NCT05971277
  lead sponsor: 
  is fda regulated drug: No
  The goal of this observational study is to collect biometric, HRQoL, immune response and
        genomic data continuously and intermittently during and after chemo or immunotherapy for the
        generation of a complex dataset using a platform which can aggregate different types of data
        collected over a time period and, to test the potential for analysis within and across data
        sets with linkage to clinical outcomes. The framework will have capabilities to integrate
        data from electronic medical records (EMRs) such as Epic, as well as digital streams
        including sensor, genomic, imaging and pathology. Such a platform can realise the potential
        for machine learning (ML) methodologies to address important cancer outcomes.
  The Investigators overarching aim is to determine the relationship between measures of
        physical performance status including heart rate and steps, health related quality of life
        (HRQoL) and genomic and immunogenomic phenotype on cancer outcomes in patients receiving
        chemotherapy or immunotherapy for haematological or metastatic cancer including renal
        (papillary, and RCC), breast, prostate, and other solid tumours. The primary objective is to
        test the feasibility of integrating diverse data streams (genomic, HR QoL and biometric) on a
        novel platform, capable of integrating data streams thus generating complex datasets for
        analyses using machine learning methodologies.
  
        Secondary objectives will be to conduct exploratory analysis assessing the relationship
        between individual and combined data types and cancer outcomes.
  
        Analysis using existing and novel computational models will be applied to the data to events
        in the acute and chronic setting that are common in patients diagnosed with cancer undergoing
        systemic therapy such as chemotherapy and immunotherapy. The outputs from this study will
        help inform future studies and trials designed to inform patients about their health status
        during cancer therapy
  observational model: Cohort
  time perspective: Prospective
  measure: Primary Objective
  time frame: one month to 52 weeks
  description: To measure feasibility of data collection longitudinally in a patient cohort undergoing systemic therapy for metastatic or haematological cancer.
  measure: Remote monitoring data
  time frame: one month to 52 weeks
  description: To collect activity (steps) and heart rate data. This will be collected using the Ethera Wellness app which participants will download onto their smartphone devices.
  measure: Biological sample data. This will include blood samples (30mls) maximum frequency will be monthly
  time frame: one month to 52 weeks
  description: This will include blood samples (30mls) and stool samples maximum frequency will be monthly
  measure: Clinical Outcome data
  time frame: one month to 52 weeks
  description: Data will be collected via an electronic case report form-
  measure: Quality of life Questionnaire
  time frame: one month to 52 weeks
  description: EORTC QLQ C30- questionnaire will be collected monthly
  intervention type: Device
  intervention name: Halo Wearable data device
  description: A wrist-worn tracker with heart-rate monitor and pedometer (step counter), as well as a mobile app.
  Genomic and microbiome analysis, statistical analysis
  study pop: 
  sampling method: Probability Sample
  criteria: 
  gender: All
  minimum age: 18 Years
  maximum age: N/A
  healthy volunteers: No
  last name: John D Kelly, Professor
  phone: 07549152902
  email: j.d.kelly@ucl.ac.uk
  last name: Hazel McBain
  phone: 07342976009
  email: hazelmcbain@nhs.net
  facility: 
  status: Recruiting
  contact: 
  contact backup: 
  country: United Kingdom
  responsible party type: Sponsor
  mesh term: Neoplasms