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/NCT06036563</url>
    </required_header>
    <id_info>
      <org_study_id>KY20232260-F-1</org_study_id>
      <nct_id>NCT06036563</nct_id>
    </id_info>
    <brief_title>Prospective Screening and Differentiating Common Cancers Using Peripheral Blood Cell-Free DNA Sequencing</brief_title>
    <official_title>A Multicenter Prospective Diagnostic Test: Screening and Differentiating Common Cancers (Cancers of Lung, Stomach, Colorectum, Esophagus, Liver, Breast and Pancreas) Based on Peripheral Blood Cell-Free DNA Sequencing</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Air Force Military Medical University, China</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>Tang-Du Hospital</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>The First Affiliated Hospital of Guangzhou Medical University</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>First Hospital of China Medical University</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>People's Hospital of Ningxia Hui Autonomous Region</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>Xinjiang Medical University</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>Guanxian People's Hospital</agency>
        <agency_class>Other</agency_class>
      </collaborator>
    </sponsors>
    <source>Air Force Military Medical University, China</source>
    <oversight_info>
      <has_dmc>Yes</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 goal of this observational study is to screen and differentiate common cancers in&#xD;
        participants with or without suspicious lesions. The main question we aim to answer is: Can&#xD;
        our developed model, using peripheral blood cell-free DNA sequencing, work well in screening&#xD;
        and classifying common cancers especially in their early stages? Participants will undergo&#xD;
        the collection of 15~20ml of blood and 1~2 telephone follow-up calls.&#xD;
      </textblock>
    </brief_summary>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">September 2023</start_date>
    <completion_date type="Anticipated">December 2025</completion_date>
    <primary_completion_date type="Anticipated">August 2025</primary_completion_date>
    <study_type>Observational [Patient Registry]</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>
    <target_duration>1 Year</target_duration>
    <primary_outcome>
      <measure>diagnostic accuracy</measure>
      <time_frame>Immediately after test completion</time_frame>
      <description>This refers to the ability of the test to correctly classify individuals into the categories of having or not having the disease. It is a measure of the test's overall effectiveness. The reference test is histological test for cancers or one-year follow-up for non-cancers.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>sensitivity</measure>
      <time_frame>Immediately after test completion</time_frame>
      <description>This is the ability of the test to correctly identify those with the disease. It is the proportion of true positive results (those with the disease who test positive) to the total number of individuals who actually have the disease. The reference test is histological test for cancers or one-year follow-up for non-cancers.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>specificity</measure>
      <time_frame>Immediately after test completion</time_frame>
      <description>This is the ability of the test to correctly identify those without the disease. It is the proportion of true negative results (those without the disease who test negative) to the total number of individuals who actually do not have the disease. The reference test is histological test for cancers or one-year follow-up for non-cancers.</description>
    </primary_outcome>
    <number_of_groups>1</number_of_groups>
    <enrollment type="Anticipated">3200</enrollment>
    <condition>Cancer Diagnosis</condition>
    <condition>LungCancer</condition>
    <condition>Gastric Cancer</condition>
    <condition>Liver Cancer</condition>
    <condition>Colorectal Cancer</condition>
    <condition>Esophagus Cancer</condition>
    <condition>Breast Cancer</condition>
    <condition>Pancreas Cancer</condition>
    <arm_group>
      <arm_group_label>Multicenter prospective cancer-screening cohort</arm_group_label>
      <description>The cohort, including cancer patients and non-cancer patients, will be prospectively enrolled in from different departments and centers. The focused cancers include lung cancer, gastric cancer, colorectal cancer, liver cancer, esophagus cancer, breast cancer and pancreas cancer.</description>
    </arm_group>
    <biospec_retention>Samples With DNA</biospec_retention>
    <biospec_descr>
      <textblock>
        15~20ml peripheral venous blood sample from each participant.&#xD;
      </textblock>
    </biospec_descr>
    <eligibility>
      <study_pop>
        <textblock>
          PASS 21.0 is used to calculate the sample size for diagnostic tests. Based on the&#xD;
          specificity and sensitivity of different cancer diagnoses in current and reported studies,&#xD;
          the specificity is preset at 98%, and the sensitivity is preset at 75%. A two-sided test is&#xD;
          chosen, with a confidence level of 1-α=0.9, and a confidence interval width of 10%. The&#xD;
          minimum sample size for the diagnostic test is calculated as follows: each type of cancer&#xD;
          should have no less than 202 cases in the diagnostic test, and the total number of cancer&#xD;
          subjects should not be less than 1414. The ratio of cancer subjects to non-cancer subjects&#xD;
          is set at 1:1. Considering the possibility of loss to follow-up, unqualified sample&#xD;
          quality, and dropout during the study, the sample size for this study is preset at 3200.&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Non-Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            1. &gt;20 and &lt; 80 years old.&#xD;
  &#xD;
            2. Cancer group: Newly diagnosed cancer patients with a confirmed pathological diagnosis&#xD;
               within 90 days before blood collection or within 30 days after blood collection,&#xD;
               including lung cancer, esophageal cancer, breast cancer, stomach cancer, colorectal&#xD;
               cancer, liver cancer, and pancreatic cancer.&#xD;
  &#xD;
          Non-cancer group: Individuals who have not been diagnosed with cancer during routine&#xD;
          physical examinations and one-year follow-up.&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            1. Uncontrolled or active systemic diseases, such as autoimmune diseases, tuberculosis,&#xD;
               AIDS, etc.&#xD;
  &#xD;
            2. New onset, recurrence, or exacerbation of various inflammations within 2 weeks before&#xD;
               blood collection, or the presence of fever, use of corticosteroids.&#xD;
  &#xD;
            3. New onset or exacerbation of thromboembolic diseases, hemorrhagic diseases, or those&#xD;
               who have received allogeneic blood transfusion within 1 month before blood collection.&#xD;
  &#xD;
            4. Any cancer treatment performed within the past 3 years.&#xD;
  &#xD;
            5. Individuals who have undergone organ or bone marrow transplantation.&#xD;
  &#xD;
            6. Participants during pregnancy or lactation.&#xD;
  &#xD;
            7. Individuals with malnutrition, severe mental illness, or genetic diseases.&#xD;
  &#xD;
            8. Other diseases or conditions deemed by the physician as unsuitable for participation&#xD;
               in this study.&#xD;
  &#xD;
            9. Individuals who are unable to sign an informed consent form.&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>20 Years</minimum_age>
      <maximum_age>80 Years</maximum_age>
      <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
    </eligibility>
    <overall_contact>
      <last_name>Yanglin Pan, MD</last_name>
      <phone>86-13991811225</phone>
      <email>panyl@fmmu.edu.cn</email>
    </overall_contact>
    <location>
      <facility>
        <name>Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University</name>
        <address>
          <city>Guangzhou</city>
          <state>Guangdong</state>
          <zip>510000</zip>
          <country>China</country>
        </address>
      </facility>
      <contact>
        <last_name>Fengxia Gan, PhD</last_name>
        <phone>86-18810532592</phone>
      </contact>
      <investigator>
        <last_name>Yaping Yang, MD</last_name>
        <role>Principal Investigator</role>
      </investigator>
      <investigator>
        <last_name>Fengxia Gan, PhD</last_name>
        <role>Sub-Investigator</role>
      </investigator>
      <investigator>
        <last_name>Changzhen Shang, MD</last_name>
        <role>Sub-Investigator</role>
      </investigator>
    </location>
    <location>
      <facility>
        <name>The First Affiliated Hospital of Guangzhou Medical University</name>
        <address>
          <city>Guangzhou</city>
          <state>Guangdong</state>
          <zip>510000</zip>
          <country>China</country>
        </address>
      </facility>
    </location>
    <location>
      <facility>
        <name>First Hospital of China Medical University</name>
        <address>
          <city>Shenyang</city>
          <state>Liaoning</state>
          <zip>110000</zip>
          <country>China</country>
        </address>
      </facility>
      <contact>
        <last_name>Liping Sun, PhD</last_name>
        <phone>86-24-83282153</phone>
        <email>lpsun@cmu.edu.cn</email>
      </contact>
      <investigator>
        <last_name>Liping Sun, PhD</last_name>
        <role>Principal Investigator</role>
      </investigator>
      <investigator>
        <last_name>Yijun Wu, MM</last_name>
        <role>Sub-Investigator</role>
      </investigator>
    </location>
    <location>
      <facility>
        <name>People's Hospital of Ningxia Hui Autonomous Region</name>
        <address>
          <city>Yinchuan</city>
          <state>Ningxia</state>
          <zip>750000</zip>
          <country>China</country>
        </address>
      </facility>
      <contact>
        <last_name>Shengjuan Hu, MD</last_name>
        <email>hsj.judy@163.com</email>
      </contact>
    </location>
    <location>
      <facility>
        <name>First Affiliated Hospital of Air Force Military Medical University</name>
        <address>
          <city>Xi'an</city>
          <state>Shaanxi</state>
          <zip>710032</zip>
          <country>China</country>
        </address>
      </facility>
    </location>
    <location>
      <facility>
        <name>Tang-du Hospital</name>
        <address>
          <city>Xi'an</city>
          <state>Shaanxi</state>
          <zip>710032</zip>
          <country>China</country>
        </address>
      </facility>
      <contact>
        <last_name>Yunfeng Ni, MD</last_name>
        <phone>86-13772088014</phone>
        <email>niyunfng@fmmu.edu.cn</email>
      </contact>
      <investigator>
        <last_name>Yunfeng Ni, MD</last_name>
        <role>Principal Investigator</role>
      </investigator>
      <investigator>
        <last_name>Xiaochen Liu, MM</last_name>
        <role>Sub-Investigator</role>
      </investigator>
    </location>
    <location>
      <facility>
        <name>Guanxian People's Hospital</name>
        <address>
          <city>Liaocheng</city>
          <state>Shandong</state>
          <zip>252500</zip>
          <country>China</country>
        </address>
      </facility>
    </location>
    <location_countries>
      <country>China</country>
    </location_countries>
    <reference>
      <citation>Nikanjam M, Kato S, Kurzrock R. Liquid biopsy: current technology and clinical applications. J Hematol Oncol. 2022 Sep 12;15(1):131. doi: 10.1186/s13045-022-01351-y.</citation>
      <PMID>36096847</PMID>
    </reference>
    <reference>
      <citation>Gao Q, Lin YP, Li BS, Wang GQ, Dong LQ, Shen BY, Lou WH, Wu WC, Ge D, Zhu QL, Xu Y, Xu JM, Chang WJ, Lan P, Zhou PH, He MJ, Qiao GB, Chuai SK, Zang RY, Shi TY, Tan LJ, Yin J, Zeng Q, Su XF, Wang ZD, Zhao XQ, Nian WQ, Zhang S, Zhou J, Cai SL, Zhang ZH, Fan J. Unintrusive multi-cancer detection by circulating cell-free DNA methylation sequencing (THUNDER): development and independent validation studies. Ann Oncol. 2023 May;34(5):486-495. doi: 10.1016/j.annonc.2023.02.010. Epub 2023 Feb 26.</citation>
      <PMID>36849097</PMID>
    </reference>
    <reference>
      <citation>Jamshidi A, Liu MC, Klein EA, Venn O, Hubbell E, Beausang JF, Gross S, Melton C, Fields AP, Liu Q, Zhang N, Fung ET, Kurtzman KN, Amini H, Betts C, Civello D, Freese P, Calef R, Davydov K, Fayzullina S, Hou C, Jiang R, Jung B, Tang S, Demas V, Newman J, Sakarya O, Scott E, Shenoy A, Shojaee S, Steffen KK, Nicula V, Chien TC, Bagaria S, Hunkapiller N, Desai M, Dong Z, Richards DA, Yeatman TJ, Cohn AL, Thiel DD, Berry DA, Tummala MK, McIntyre K, Sekeres MA, Bryce A, Aravanis AM, Seiden MV, Swanton C. Evaluation of cell-free DNA approaches for multi-cancer early detection. Cancer Cell. 2022 Dec 12;40(12):1537-1549.e12. doi: 10.1016/j.ccell.2022.10.022. Epub 2022 Nov 17.</citation>
      <PMID>36400018</PMID>
    </reference>
    <reference>
      <citation>Helzer KT, Sharifi MN, Sperger JM, Shi Y, Annala M, Bootsma ML, Reese SR, Taylor A, Kaufmann KR, Krause HK, Schehr JL, Sethakorn N, Kosoff D, Kyriakopoulos C, Burkard ME, Rydzewski NR, Yu M, Harari PM, Bassetti M, Blitzer G, Floberg J, Sjostrom M, Quigley DA, Dehm SM, Armstrong AJ, Beltran H, McKay RR, Feng FY, O'Regan R, Wisinski KB, Emamekhoo H, Wyatt AW, Lang JM, Zhao SG. Fragmentomic analysis of circulating tumor DNA-targeted cancer panels. Ann Oncol. 2023 Sep;34(9):813-825. doi: 10.1016/j.annonc.2023.06.001. Epub 2023 Jun 16.</citation>
      <PMID>37330052</PMID>
    </reference>
    <reference>
      <citation>Fan R, Chen L, Zhao S, Yang H, Li Z, Qian Y, Ma H, Liu X, Wang C, Liang X, Bai J, Xie J, Fan X, Xie Q, Hao X, Wang C, Yang S, Gao Y, Bai H, Dou X, Liu J, Wu L, Jiang G, Xia Q, Zheng D, Rao H, Xia J, Shang J, Gao P, Xie D, Yu Y, Yang Y, Gao H, Liu Y, Sun A, Jiang Y, Yu Y, Niu J, Sun J, Wang H, Hou J. Novel, high accuracy models for hepatocellular carcinoma prediction based on longitudinal data and cell-free DNA signatures. J Hepatol. 2023 Jun 10:S0168-8278(23)00416-6. doi: 10.1016/j.jhep.2023.05.039. Online ahead of print.</citation>
      <PMID>37302583</PMID>
    </reference>
    <verification_date>September 2023</verification_date>
    <study_first_submitted>September 7, 2023</study_first_submitted>
    <study_first_submitted_qc>September 7, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">September 14, 2023</study_first_posted>
    <last_update_submitted>September 7, 2023</last_update_submitted>
    <last_update_submitted_qc>September 7, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">September 14, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Principal Investigator</responsible_party_type>
      <investigator_affiliation>Air Force Military Medical University, China</investigator_affiliation>
      <investigator_full_name>Yanglin Pan</investigator_full_name>
      <investigator_title>Professor</investigator_title>
    </responsible_party>
    <keyword>multicancer screening</keyword>
    <keyword>liquid biopsy</keyword>
    <keyword>cell-free DNA</keyword>
    <keyword>methylation</keyword>
    <keyword>machine learning</keyword>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Pancreatic Neoplasms</mesh_term>
      <mesh_term>Esophageal Neoplasms</mesh_term>
      <mesh_term>Lung Neoplasms</mesh_term>
    </condition_browse>
    <patient_data>
      <sharing_ipd>No</sharing_ipd>
    </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/NCT06036563
  org study id: KY20232260-F-1
  nct id: NCT06036563
  lead sponsor: 
  collaborator: 
  collaborator: 
  collaborator: 
  collaborator: 
  collaborator: 
  collaborator: 
  collaborator: 
  has dmc: Yes
  is fda regulated drug: No
  is fda regulated device: No
  The goal of this observational study is to screen and differentiate common cancers in
        participants with or without suspicious lesions. The main question we aim to answer is: Can
        our developed model, using peripheral blood cell-free DNA sequencing, work well in screening
        and classifying common cancers especially in their early stages? Participants will undergo
        the collection of 15~20ml of blood and 1~2 telephone follow-up calls.
  observational model: Cohort
  time perspective: Prospective
  measure: diagnostic accuracy
  time frame: Immediately after test completion
  description: This refers to the ability of the test to correctly classify individuals into the categories of having or not having the disease. It is a measure of the test's overall effectiveness. The reference test is histological test for cancers or one-year follow-up for non-cancers.
  measure: sensitivity
  time frame: Immediately after test completion
  description: This is the ability of the test to correctly identify those with the disease. It is the proportion of true positive results (those with the disease who test positive) to the total number of individuals who actually have the disease. The reference test is histological test for cancers or one-year follow-up for non-cancers.
  measure: specificity
  time frame: Immediately after test completion
  description: This is the ability of the test to correctly identify those without the disease. It is the proportion of true negative results (those without the disease who test negative) to the total number of individuals who actually do not have the disease. The reference test is histological test for cancers or one-year follow-up for non-cancers.
  arm group label: Multicenter prospective cancer-screening cohort
  description: The cohort, including cancer patients and non-cancer patients, will be prospectively enrolled in from different departments and centers. The focused cancers include lung cancer, gastric cancer, colorectal cancer, liver cancer, esophagus cancer, breast cancer and pancreas cancer.
  15~20ml peripheral venous blood sample from each participant.
  study pop: 
  sampling method: Non-Probability Sample
  criteria: 
  gender: All
  minimum age: 20 Years
  maximum age: 80 Years
  healthy volunteers: Accepts Healthy Volunteers
  last name: Yanglin Pan, MD
  phone: 86-13991811225
  email: panyl@fmmu.edu.cn
  facility: 
  contact: 
  investigator: 
  investigator: 
  investigator: 
  facility: 
  facility: 
  contact: 
  investigator: 
  investigator: 
  facility: 
  contact: 
  facility: 
  facility: 
  contact: 
  investigator: 
  investigator: 
  facility: 
  country: China
  citation: Nikanjam M, Kato S, Kurzrock R. Liquid biopsy: current technology and clinical applications. J Hematol Oncol. 2022 Sep 12;15(1):131. doi: 10.1186/s13045-022-01351-y.
  PMID: 36096847
  citation: Gao Q, Lin YP, Li BS, Wang GQ, Dong LQ, Shen BY, Lou WH, Wu WC, Ge D, Zhu QL, Xu Y, Xu JM, Chang WJ, Lan P, Zhou PH, He MJ, Qiao GB, Chuai SK, Zang RY, Shi TY, Tan LJ, Yin J, Zeng Q, Su XF, Wang ZD, Zhao XQ, Nian WQ, Zhang S, Zhou J, Cai SL, Zhang ZH, Fan J. Unintrusive multi-cancer detection by circulating cell-free DNA methylation sequencing (THUNDER): development and independent validation studies. Ann Oncol. 2023 May;34(5):486-495. doi: 10.1016/j.annonc.2023.02.010. Epub 2023 Feb 26.
  PMID: 36849097
  citation: Jamshidi A, Liu MC, Klein EA, Venn O, Hubbell E, Beausang JF, Gross S, Melton C, Fields AP, Liu Q, Zhang N, Fung ET, Kurtzman KN, Amini H, Betts C, Civello D, Freese P, Calef R, Davydov K, Fayzullina S, Hou C, Jiang R, Jung B, Tang S, Demas V, Newman J, Sakarya O, Scott E, Shenoy A, Shojaee S, Steffen KK, Nicula V, Chien TC, Bagaria S, Hunkapiller N, Desai M, Dong Z, Richards DA, Yeatman TJ, Cohn AL, Thiel DD, Berry DA, Tummala MK, McIntyre K, Sekeres MA, Bryce A, Aravanis AM, Seiden MV, Swanton C. Evaluation of cell-free DNA approaches for multi-cancer early detection. Cancer Cell. 2022 Dec 12;40(12):1537-1549.e12. doi: 10.1016/j.ccell.2022.10.022. Epub 2022 Nov 17.
  PMID: 36400018
  citation: Helzer KT, Sharifi MN, Sperger JM, Shi Y, Annala M, Bootsma ML, Reese SR, Taylor A, Kaufmann KR, Krause HK, Schehr JL, Sethakorn N, Kosoff D, Kyriakopoulos C, Burkard ME, Rydzewski NR, Yu M, Harari PM, Bassetti M, Blitzer G, Floberg J, Sjostrom M, Quigley DA, Dehm SM, Armstrong AJ, Beltran H, McKay RR, Feng FY, O'Regan R, Wisinski KB, Emamekhoo H, Wyatt AW, Lang JM, Zhao SG. Fragmentomic analysis of circulating tumor DNA-targeted cancer panels. Ann Oncol. 2023 Sep;34(9):813-825. doi: 10.1016/j.annonc.2023.06.001. Epub 2023 Jun 16.
  PMID: 37330052
  citation: Fan R, Chen L, Zhao S, Yang H, Li Z, Qian Y, Ma H, Liu X, Wang C, Liang X, Bai J, Xie J, Fan X, Xie Q, Hao X, Wang C, Yang S, Gao Y, Bai H, Dou X, Liu J, Wu L, Jiang G, Xia Q, Zheng D, Rao H, Xia J, Shang J, Gao P, Xie D, Yu Y, Yang Y, Gao H, Liu Y, Sun A, Jiang Y, Yu Y, Niu J, Sun J, Wang H, Hou J. Novel, high accuracy models for hepatocellular carcinoma prediction based on longitudinal data and cell-free DNA signatures. J Hepatol. 2023 Jun 10:S0168-8278(23)00416-6. doi: 10.1016/j.jhep.2023.05.039. Online ahead of print.
  PMID: 37302583
  responsible party type: Principal Investigator
  investigator affiliation: Air Force Military Medical University, China
  investigator full name: Yanglin Pan
  investigator title: Professor
  mesh term: Pancreatic Neoplasms
  mesh term: Esophageal Neoplasms
  mesh term: Lung Neoplasms
  sharing ipd: No