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/NCT05971082</url>
    </required_header>
    <id_info>
      <org_study_id>FLD_FU_HUS</org_study_id>
      <nct_id>NCT05971082</nct_id>
    </id_info>
    <brief_title>Risk Factors for Advanced Fibrosis Among FLD Patients</brief_title>
    <acronym>FLD_FU_HUS</acronym>
    <official_title>Risk Factors for Advanced Fibrosis Among Fatty Liver Disease Patients Identified Through Pharese-screening of Miaging Reports</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Helsinki University Central Hospital</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>Pfizer</agency>
        <agency_class>Industry</agency_class>
      </collaborator>
    </sponsors>
    <source>Helsinki University Central Hospital</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 investigators investigate the heterogeneity fatty liver disease (FLD) as well as risk&#xD;
        factors associated with progression of the liver diseases or development of cardiovascular&#xD;
        complication. The overarching aim is to develop a AI-based prediction model that could be&#xD;
        integrated into the electronic medical record system.&#xD;
  &#xD;
        To identify large numbers of unselected individuals with FLD, the investigators developed a&#xD;
        phrase recognition algorithm, which identifies FLD using radiology reports. Within the data&#xD;
        lake of Helsinki University Hospital, they identified a large number of individuals with or&#xD;
        without FLD. The investigators will now randomly invite 1000-1500 individuals with FLD to a&#xD;
        follow-up study including investigation of metabolism and progression of liver disease&#xD;
        (elastography, blood tests) as well as gathering life-style information. Register data on&#xD;
        previous diagnoses and medication will be used to evaluate cardiovascular disease.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        The investigators investigate the heterogeneity fatty liver disease (FLD) as well as risk&#xD;
        factors associated with progression of the liver diseases or development of cardiovascular&#xD;
        complication. The overarching aim is to develop a AI-based prediction model that could be&#xD;
        integrated into the electronic medical record system.&#xD;
  &#xD;
        To identify large numbers of unselected individuals with FLD, the investigators developed a&#xD;
        phrase recognition algorithm, which identifies FLD using radiology reports. This allows them&#xD;
        to study also individuals who have had abdominal imaging for any reason (usually not for&#xD;
        suspected liver disease). Within the data lake of Helsinki University Hospital, the&#xD;
        investigators identified 61,271 individuals with FLD and 155,521 without. The investigators&#xD;
        have obtained national register data on their diagnosed diseases and medication.&#xD;
  &#xD;
        The investigators will now invite a random sample of 1000-1500 individuals with FLD (aged&#xD;
        20-60 years at the time of the previous imaging) to a follow-up study. Progression of liver&#xD;
        disease will be studied by elastography, measurement of fat content and a blood sample for&#xD;
        fibrosis markes (ELF score). The participants' metabolism will be evaluated with several&#xD;
        laboraroty tests and an i.v. glucagon tolerance test and amino acid response. Questionnaires&#xD;
        will be used to obtain life-style information.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">August 15, 2023</start_date>
    <completion_date type="Anticipated">December 31, 2025</completion_date>
    <primary_completion_date type="Anticipated">December 31, 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>Other</time_perspective>
    </study_design_info>
    <primary_outcome>
      <measure>Progression of liver disease</measure>
      <time_frame>5-15 years</time_frame>
      <description>Proportion of participants who have developed liver fibrosis or steatosis since the index date (in 2010-2018)</description>
    </primary_outcome>
    <primary_outcome>
      <measure>remission of fatty liver disease</measure>
      <time_frame>5-15 years</time_frame>
      <description>Proportion of participants with remission of fatty liver (= no detectable liver fat) since the index date (in 2010-2018)</description>
    </primary_outcome>
    <number_of_groups>1</number_of_groups>
    <enrollment type="Anticipated">1000</enrollment>
    <condition>NAFLD</condition>
    <condition>Liver Cirrhosis</condition>
    <condition>Diabetes Mellitus, Type 2</condition>
    <arm_group>
      <arm_group_label>Recall study</arm_group_label>
      <description>Recruited individuals aged 20-60 at index imaging date invited for follow-up with liver elastography and fat prosentage measurement</description>
    </arm_group>
    <intervention>
      <intervention_type>Other</intervention_type>
      <intervention_name>Follow-up</intervention_name>
      <description>Follow-up study of progression/remission of liver disease</description>
      <arm_group_label>Recall study</arm_group_label>
    </intervention>
    <biospec_retention>Samples With DNA</biospec_retention>
    <biospec_descr>
      <textblock>
        Blood and urine samples, blood DNA and RNA&#xD;
      </textblock>
    </biospec_descr>
    <eligibility>
      <study_pop>
        <textblock>
          The investigators will invite a random sample of 1000-1500 individuals with FLD (aged 20-60&#xD;
          years at the time of the previous imaging) to a follow-up study. See eligibility criteria&#xD;
          for details.&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Non-Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Liver imaging results in the Helsinki University Hospital datalake 2010-2018 and a&#xD;
               finding of fatty liver disease (without liver cirrhosis)&#xD;
  &#xD;
            -  Age 20-60 years at the time of the index imaging (2010-2018)&#xD;
  &#xD;
            -  Biobank consent with the Helsinki Biobank to be contacted for possible studies&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
          Liver cirrhosis at index imaging date; pregnancy; active treatment for cancer&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>20 Years</minimum_age>
      <maximum_age>70 Years</maximum_age>
      <healthy_volunteers>No</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Tiinamaija Tuomi, MD, PhD</last_name>
      <role>Study Director</role>
      <affiliation>Chief Physician</affiliation>
    </overall_official>
    <overall_contact>
      <last_name>Tiinamaija Tuomi, MD, PhD</last_name>
      <phone>+358504279013</phone>
      <email>tiinamaija.tuomi@hus.fi</email>
    </overall_contact>
    <verification_date>August 2023</verification_date>
    <study_first_submitted>June 29, 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>August 1, 2023</last_update_submitted>
    <last_update_submitted_qc>August 1, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 3, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Principal Investigator</responsible_party_type>
      <investigator_affiliation>Helsinki University Central Hospital</investigator_affiliation>
      <investigator_full_name>Tiinamaija Tuomi</investigator_full_name>
      <investigator_title>Chief Physician</investigator_title>
    </responsible_party>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Liver Cirrhosis</mesh_term>
      <mesh_term>Diabetes Mellitus, Type 2</mesh_term>
    </condition_browse>
    <patient_data>
      <sharing_ipd>No</sharing_ipd>
      <ipd_description>Data can be requested from the HUS University Hospital</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/NCT05971082
  org study id: FLD_FU_HUS
  nct id: NCT05971082
  lead sponsor: 
  collaborator: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  The investigators investigate the heterogeneity fatty liver disease (FLD) as well as risk
        factors associated with progression of the liver diseases or development of cardiovascular
        complication. The overarching aim is to develop a AI-based prediction model that could be
        integrated into the electronic medical record system.
  
        To identify large numbers of unselected individuals with FLD, the investigators developed a
        phrase recognition algorithm, which identifies FLD using radiology reports. Within the data
        lake of Helsinki University Hospital, they identified a large number of individuals with or
        without FLD. The investigators will now randomly invite 1000-1500 individuals with FLD to a
        follow-up study including investigation of metabolism and progression of liver disease
        (elastography, blood tests) as well as gathering life-style information. Register data on
        previous diagnoses and medication will be used to evaluate cardiovascular disease.
  The investigators investigate the heterogeneity fatty liver disease (FLD) as well as risk
        factors associated with progression of the liver diseases or development of cardiovascular
        complication. The overarching aim is to develop a AI-based prediction model that could be
        integrated into the electronic medical record system.
  
        To identify large numbers of unselected individuals with FLD, the investigators developed a
        phrase recognition algorithm, which identifies FLD using radiology reports. This allows them
        to study also individuals who have had abdominal imaging for any reason (usually not for
        suspected liver disease). Within the data lake of Helsinki University Hospital, the
        investigators identified 61,271 individuals with FLD and 155,521 without. The investigators
        have obtained national register data on their diagnosed diseases and medication.
  
        The investigators will now invite a random sample of 1000-1500 individuals with FLD (aged
        20-60 years at the time of the previous imaging) to a follow-up study. Progression of liver
        disease will be studied by elastography, measurement of fat content and a blood sample for
        fibrosis markes (ELF score). The participants' metabolism will be evaluated with several
        laboraroty tests and an i.v. glucagon tolerance test and amino acid response. Questionnaires
        will be used to obtain life-style information.
  observational model: Cohort
  time perspective: Other
  measure: Progression of liver disease
  time frame: 5-15 years
  description: Proportion of participants who have developed liver fibrosis or steatosis since the index date (in 2010-2018)
  measure: remission of fatty liver disease
  time frame: 5-15 years
  description: Proportion of participants with remission of fatty liver (= no detectable liver fat) since the index date (in 2010-2018)
  arm group label: Recall study
  description: Recruited individuals aged 20-60 at index imaging date invited for follow-up with liver elastography and fat prosentage measurement
  intervention type: Other
  intervention name: Follow-up
  description: Follow-up study of progression/remission of liver disease
  arm group label: Recall study
  Blood and urine samples, blood DNA and RNA
  study pop: 
  sampling method: Non-Probability Sample
  criteria: 
  gender: All
  minimum age: 20 Years
  maximum age: 70 Years
  healthy volunteers: No
  last name: Tiinamaija Tuomi, MD, PhD
  role: Study Director
  affiliation: Chief Physician
  last name: Tiinamaija Tuomi, MD, PhD
  phone: +358504279013
  email: tiinamaija.tuomi@hus.fi
  responsible party type: Principal Investigator
  investigator affiliation: Helsinki University Central Hospital
  investigator full name: Tiinamaija Tuomi
  investigator title: Chief Physician
  mesh term: Liver Cirrhosis
  mesh term: Diabetes Mellitus, Type 2
  sharing ipd: No
  ipd description: Data can be requested from the HUS University Hospital