<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/NCT04477798</url>
  </required_header>
  <id_info>
    <org_study_id>ZhejiangU20200701</org_study_id>
    <nct_id>NCT04477798</nct_id>
  </id_info>
  <brief_title>Protein Classifier for Thyroid Indeterminate Nodules</brief_title>
  <official_title>Protein Classifier for Thyroid Indeterminate Nodules： a Multi-center Prospective Clinical Study</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Luo Dingcun</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Zhejiang University</source>
  <oversight_info>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      In multi-center, prospective, double-blind cohorts, PCT-DIA/MS protein classifier supported&#xD;
      by artificial neural networks will be validated to classify thyroid indeterminate nodules.&#xD;
    </textblock>
  </brief_summary>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Recruiting</last_known_status>
  <start_date type="Anticipated">August 1, 2020</start_date>
  <completion_date type="Anticipated">December 31, 2021</completion_date>
  <primary_completion_date type="Anticipated">July 1, 2021</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>Diagnostic</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>protein classifier</measure>
    <time_frame>immediately after the procedure</time_frame>
    <description>classify thyroid indeterminate nodules as Benign or Malignant</description>
  </primary_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Anticipated">320</enrollment>
  <condition>Thyroid Nodule</condition>
  <arm_group>
    <arm_group_label>PCT-DIA/MS</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>PCT-DIA/MS protein classifier supported by artificial neural networks will be validated to classify thyroid indeterminate nodules</description>
  </arm_group>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>PCT-DIA/MS</intervention_name>
    <description>PCT-DIA/MS will be validated to classify FNA biopsy specimens</description>
    <arm_group_label>PCT-DIA/MS</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          1. Patients with aged 18 to 70 years old;&#xD;
&#xD;
          2. Patients with thyroid nodules who have not been treated with drugs;&#xD;
&#xD;
          3. Patients who were diagnosed as Bethesda III and IV by cytology and pathology before&#xD;
             operation;&#xD;
&#xD;
          4. Patients who underwent total / partial thyroidectomy and had histopathological reports&#xD;
             of corresponding cellular pathological punctured nodules;&#xD;
&#xD;
          5. Patients voluntarily participate in the study after informed consent.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          1. Patients without operation;&#xD;
&#xD;
          2. Patients with insufficient FNA sample size (judged by the laboratory).&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>70 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Dingcun Luo</last_name>
    <role>Principal Investigator</role>
    <affiliation>First People's Hospital of Hangzhou</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Dingcun Luo</last_name>
    <phone>+86057156005600</phone>
    <email>wlsydxjk@163.com</email>
  </overall_contact>
  <location>
    <facility>
      <name>Hangzhou First People's Hospital Affiliated to Zhejiang University Medical College</name>
      <address>
        <city>Hangzhou</city>
        <state>Zhejiang</state>
        <zip>317500</zip>
        <country>China</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Dingcun Luo</last_name>
    </contact>
  </location>
  <location_countries>
    <country>China</country>
  </location_countries>
  <verification_date>July 2020</verification_date>
  <study_first_submitted>July 10, 2020</study_first_submitted>
  <study_first_submitted_qc>July 16, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">July 20, 2020</study_first_posted>
  <last_update_submitted>July 16, 2020</last_update_submitted>
  <last_update_submitted_qc>July 16, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">July 20, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor-Investigator</responsible_party_type>
    <investigator_affiliation>Zhejiang University</investigator_affiliation>
    <investigator_full_name>Luo Dingcun</investigator_full_name>
    <investigator_title>vice president of hospital</investigator_title>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Thyroid Nodule</mesh_term>
    <mesh_term>Thyroid Diseases</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


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/NCT04477798
org study id: ZhejiangU20200701
nct id: NCT04477798
lead sponsor: 
is fda regulated drug: No
is fda regulated device: No
In multi-center, prospective, double-blind cohorts, PCT-DIA/MS protein classifier supported
      by artificial neural networks will be validated to classify thyroid indeterminate nodules.
allocation: N/A
intervention model: Single Group Assignment
primary purpose: Diagnostic
masking: None (Open Label)
measure: protein classifier
time frame: immediately after the procedure
description: classify thyroid indeterminate nodules as Benign or Malignant
arm group label: PCT-DIA/MS
arm group type: Experimental
description: PCT-DIA/MS protein classifier supported by artificial neural networks will be validated to classify thyroid indeterminate nodules
intervention type: Diagnostic Test
intervention name: PCT-DIA/MS
description: PCT-DIA/MS will be validated to classify FNA biopsy specimens
arm group label: PCT-DIA/MS
criteria: 
gender: All
minimum age: 18 Years
maximum age: 70 Years
healthy volunteers: No
last name: Dingcun Luo
role: Principal Investigator
affiliation: First People's Hospital of Hangzhou
last name: Dingcun Luo
phone: +86057156005600
email: wlsydxjk@163.com
facility: 
status: Recruiting
contact: 
country: China
responsible party type: Sponsor-Investigator
investigator affiliation: Zhejiang University
investigator full name: Luo Dingcun
investigator title: vice president of hospital
mesh term: Thyroid Nodule
mesh term: Thyroid Diseases
sharing ipd: No