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/NCT06029452</url>
    </required_header>
    <id_info>
      <org_study_id>B3461111</org_study_id>
      <nct_id>NCT06029452</nct_id>
    </id_info>
    <brief_title>A Retrospective Validation Study To Identify Chart-Based Clinical Diagnosis Of Wild-Type Transthyretin Amyloid Cardiomyopathy (Attrwt-CM) And Non-Amyloid Heart Failure Among Patients With Heart Failure (HF).</brief_title>
    <official_title>A Retrospective Chart Validation Study Evaluating The Performance Of Machine Learning Algorithm (ML) To Predict The Clinical Diagnosis Of Wild-Type Transthyretin Amyloid Cardiomyopathy (Attrwt-CM) And Non-Amyloid Heart Failure Among Patients With Heart Failure (HF)</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Pfizer</agency>
        <agency_class>Industry</agency_class>
      </lead_sponsor>
    </sponsors>
    <source>Pfizer</source>
    <brief_summary>
      <textblock>
        This is an observational, retrospective non-inferiority study with a study sample from a&#xD;
        large national database.&#xD;
  &#xD;
        A machine learning (ML) model will use a national database to predict the clinical diagnosis&#xD;
        of ATTRwt-CM among HF patients. This study will include HF patients ≥50 years old.&#xD;
      </textblock>
    </brief_summary>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">September 2, 2023</start_date>
    <completion_date type="Anticipated">October 31, 2023</completion_date>
    <primary_completion_date type="Anticipated">October 31, 2023</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>Retrospective</time_perspective>
    </study_design_info>
    <primary_outcome>
      <measure>The total number of clinically diagnosed patients using the ML algorithm</measure>
      <time_frame>60 days</time_frame>
      <description>to evaluate the performance of the ATTRwt-CM ML model to predict the clinical diagnosis of ATTRwt-CM among HF patients against chart-review-based ground truth with a prespecified performance thresholds in sensitivity and specificity.</description>
    </primary_outcome>
    <number_of_groups>1</number_of_groups>
    <enrollment type="Anticipated">844</enrollment>
    <condition>ATTR-CM</condition>
    <arm_group>
      <arm_group_label>ATTRwt-CM and non-amyloid heart failure patients</arm_group_label>
    </arm_group>
    <intervention>
      <intervention_type>Other</intervention_type>
      <intervention_name>Machine learning algorithm</intervention_name>
      <description>Software to calculate the predicted probability of ATTRwt-CM for these heart failure patients based on the presence and absence of certain features</description>
      <arm_group_label>ATTRwt-CM and non-amyloid heart failure patients</arm_group_label>
    </intervention>
    <eligibility>
      <study_pop>
        <textblock>
          Heart failure patients with clinical diagnosis of ATTRwt-CM or non-amyloid HF&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Non-Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  HF patients (defined as having ≥1 claim for HF or HF treatment) ≥50 years old with&#xD;
               clinical diagnosis of ATTRwt-CM or non-amyloid HF ascertained by charts. Patients will&#xD;
               be required to have ≥12 months of continuous activity in the EHR or claims prior to&#xD;
               the Index Date.&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  Patients with any of the following diagnoses:&#xD;
  &#xD;
                 -  Light chain (AL) amyloidosis&#xD;
  &#xD;
                 -  Intracranial hemorrhage&#xD;
  &#xD;
                 -  Cerebral amyloid angiopathy&#xD;
  &#xD;
                 -  End stage renal disease&#xD;
  &#xD;
                 -  Blood cancer&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>50 Years</minimum_age>
      <maximum_age>N/A</maximum_age>
      <healthy_volunteers>No</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Pfizer CT.gov Call Center</last_name>
      <role>Study Director</role>
      <affiliation>Pfizer</affiliation>
    </overall_official>
    <overall_contact>
      <last_name>Pfizer CT.gov Call Center</last_name>
      <phone>1-800-718-1021</phone>
      <email>ClinicalTrials.gov_Inquiries@pfizer.com</email>
    </overall_contact>
    <location>
      <facility>
        <name>Pfizer</name>
        <address>
          <city>New York</city>
          <state>New York</state>
          <zip>10018</zip>
          <country>United States</country>
        </address>
      </facility>
    </location>
    <location_countries>
      <country>United States</country>
    </location_countries>
    <verification_date>September 2023</verification_date>
    <study_first_submitted>September 1, 2023</study_first_submitted>
    <study_first_submitted_qc>September 1, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">September 8, 2023</study_first_posted>
    <last_update_submitted>September 1, 2023</last_update_submitted>
    <last_update_submitted_qc>September 1, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">September 8, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <keyword>Chronic Heart Failure</keyword>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Heart Failure</mesh_term>
      <mesh_term>Cardiomyopathies</mesh_term>
    </condition_browse>
    <patient_data>
      <sharing_ipd>No</sharing_ipd>
      <ipd_description>Pfizer will provide access to individual de-identified participant data and related study documents (e.g. protocol, Statistical Analysis Plan (SAP), Clinical Study Report (CSR)) upon request from qualified researchers, and subject to certain criteria, conditions, and exceptions. Further details on Pfizer's data sharing criteria and process for requesting access can be found at: https://www.pfizer.com/science/clinical_trials/trial_data_and_results/data_requests.</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/NCT06029452
  org study id: B3461111
  nct id: NCT06029452
  lead sponsor: 
  This is an observational, retrospective non-inferiority study with a study sample from a
        large national database.
  
        A machine learning (ML) model will use a national database to predict the clinical diagnosis
        of ATTRwt-CM among HF patients. This study will include HF patients ≥50 years old.
  observational model: Cohort
  time perspective: Retrospective
  measure: The total number of clinically diagnosed patients using the ML algorithm
  time frame: 60 days
  description: to evaluate the performance of the ATTRwt-CM ML model to predict the clinical diagnosis of ATTRwt-CM among HF patients against chart-review-based ground truth with a prespecified performance thresholds in sensitivity and specificity.
  arm group label: ATTRwt-CM and non-amyloid heart failure patients
  intervention type: Other
  intervention name: Machine learning algorithm
  description: Software to calculate the predicted probability of ATTRwt-CM for these heart failure patients based on the presence and absence of certain features
  arm group label: ATTRwt-CM and non-amyloid heart failure patients
  study pop: 
  sampling method: Non-Probability Sample
  criteria: 
  gender: All
  minimum age: 50 Years
  maximum age: N/A
  healthy volunteers: No
  last name: Pfizer CT.gov Call Center
  role: Study Director
  affiliation: Pfizer
  last name: Pfizer CT.gov Call Center
  phone: 1-800-718-1021
  email: ClinicalTrials.gov_Inquiries@pfizer.com
  facility: 
  country: United States
  responsible party type: Sponsor
  mesh term: Heart Failure
  mesh term: Cardiomyopathies
  sharing ipd: No
  ipd description: Pfizer will provide access to individual de-identified participant data and related study documents (e.g. protocol, Statistical Analysis Plan (SAP), Clinical Study Report (CSR)) upon request from qualified researchers, and subject to certain criteria, conditions, and exceptions. Further details on Pfizer's data sharing criteria and process for requesting access can be found at: https://www.pfizer.com/science/clinical_trials/trial_data_and_results/data_requests.