<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/NCT03029793</url>
  </required_header>
  <id_info>
    <org_study_id>XJFL-2016-ESO</org_study_id>
    <nct_id>NCT03029793</nct_id>
  </id_info>
  <brief_title>Biomarkers and Functional Imaging in Predicting Response of Esophageal Cancer</brief_title>
  <official_title>Combination of Molecular Biomarkers and Functional Imaging in Predicting Pathologic Response and Clinical Outcomes in Squamous Esophageal Cancer Patients Who Undergo Trimodality Therapy</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Air Force Military Medical University, China</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Air Force Military Medical University, China</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
  </oversight_info>
  <brief_summary>
    <textblock>
      The purpose of this study is to determine whether combination of molecular and biomarkers&#xD;
      with functional imaging can predict pathologic response and clinical outcomes in squamous&#xD;
      esophageal cancer patients who undergo trimodality therapy which includes neoadjuvant&#xD;
      chemoradiotherapy and surgery&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The recommended care for the management of locally advanced esophageal cancers is neoadjuvant&#xD;
      chemoradiotherapy (nCRT) followed by esophagectomy based on the NCCN guideline. The rate of&#xD;
      pathologic complete response (pCR) after nCRT was around 25-30%, reflecting potential cure of&#xD;
      unresectable esophageal cancer receiving CRT. Since esophagectomy might have substantial&#xD;
      morbidity and mortality rate, establishing the model for predicting nCRT response and&#xD;
      survival will guide neoadjuvant treatment decisions and personalized treatment. Thus surgery&#xD;
      might be spared in some patients with complete responses after nCRT, and surgery could be&#xD;
      selectively reserved for those with only partial or no response to CRT. However, reported&#xD;
      models yield unsatisfactory results due to small sample size and low accuracy, and most cases&#xD;
      were adenocarcinoma and few models were used to predict survival. This study will&#xD;
      prospectively collect the tissue and blood samples of locally advanced esophageal cancer&#xD;
      patients, detect CRT resistance biomarkers, assess the SUV value and texture parameters of&#xD;
      18F-FDG PET-CT as well as ADC values DWI-MRI. The investigators will use advanced statistical&#xD;
      tools to establish the model and further validate the model in another group of patients.The&#xD;
      investigators will also establish a model for survival prediction. This model might possibly&#xD;
      guide the personalized treatment for esophageal squamous cell carcinoma patients in China.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Recruiting</last_known_status>
  <start_date>May 2016</start_date>
  <completion_date type="Anticipated">January 2020</completion_date>
  <primary_completion_date type="Anticipated">January 2019</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>Pathologic Response</measure>
    <time_frame>Approximately 12 months</time_frame>
    <description>Mandard tumor regression grade (TRG) was used for pathology analysis. Primary tumor and positive lymph node regression were classified into five histologic tumor regression grades. Grade 1 (complete regression) showed absence of histologically identifiable residual cancer and fibrosis extending through the different layers of the esophageal wall, with or without granuloma. Grade 2 was characterized by the presence of rare residual cancer cells scattered through the fibrosis. Grade 3 involved an increase in the number of residual cancer cells, but fibrosis still predominated. Grade 4 showed residual cancer outgrowing fibrosis. Grade 5 was characterized by the absence of regressive changes.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Overall Survival</measure>
    <time_frame>Approximately 4 years</time_frame>
  </secondary_outcome>
  <number_of_groups>1</number_of_groups>
  <enrollment type="Anticipated">200</enrollment>
  <condition>Esophageal Cancer</condition>
  <arm_group>
    <arm_group_label>Biomarkers and Imaging analysis</arm_group_label>
    <description>This study will prospectively collect the tissue and blood samples of locally advanced esophageal cancer patients, perform CRT resistance biomarkers testing and functional imaging analysis including SUV value and texture parameters of 18F-FDG PET-CT as well as ADC values DWI-MRI before treatment, 2-3 weeks after the initiation of CRT, and 4 weeks post-nCRT. The investigators will use advanced statistical tools to establish the model and further validate the model in another group of patients. The investigators will also establish a model for survival prediction.</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Biomarkers Testing</intervention_name>
    <description>CRT resistance biomarkers will be detected before CRT, 2-3 weeks after the initiation of CRT, and 4 weeks post-CRT.</description>
    <arm_group_label>Biomarkers and Imaging analysis</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Functional Imaging analysis</intervention_name>
    <description>The SUV value and texture parameters of 18F-FDG PET-CT as well as ADC values DWI-MRI will be measures before CRT, 2-3 weeks after the initiation of CRT, and 4 weeks post-CRT.</description>
    <arm_group_label>Biomarkers and Imaging analysis</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        Patients with localized carcinoma of the esophagus&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          1. Patient must have histologic documentation of squamous carcinoma of the esophagus at&#xD;
             Xijing Hospital.&#xD;
&#xD;
          2. Newly diagnosed Patients with localized carcinoma of the esophagus who have undergone&#xD;
             standard testing and been evaluated by the multidisciplinary team at Xijing Hospital&#xD;
             and are considered appropriate candidates for and are willing to undergo&#xD;
             chemoradiotherapy followed by surgery at Xijing Hospital.&#xD;
&#xD;
          3. Patient must have undergone a baseline esophageal-gastroduodenoscopy (EGD) with biopsy&#xD;
             and endoscopic ultrasonography at Xijing, with tissue available for biomarker&#xD;
             analysis.&#xD;
&#xD;
          4. Patient must be willing to undergo this research and must provide written informed&#xD;
             consent.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          1. Patient is unable or unwilling to comply with the requirements of the protocol.&#xD;
&#xD;
          2. History of prior malignancy within the past 3 years.&#xD;
&#xD;
          3. Patients with second primary tumors.&#xD;
&#xD;
          4. Patients who received endoscopical therapy or induction chemotherapy prior to&#xD;
             chemoradiation therapy are excluded.&#xD;
&#xD;
          5. Patient is not a candidate for chemoradiation followed by surgery.&#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>Mei Shi, MD</last_name>
    <role>Study Chair</role>
    <affiliation>Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Li-Na Zhao, MD, Ph.D</last_name>
    <phone>+86-29-84775425</phone>
    <email>zhaolinazln@outlook.com</email>
  </overall_contact>
  <location>
    <facility>
      <name>Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University</name>
      <address>
        <city>Xi'an</city>
        <state>Shaanxi</state>
        <zip>710032</zip>
        <country>China</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Lina Zhao, MD, Ph.D</last_name>
      <phone>+86-029-84775425</phone>
      <email>zhaolinazln@outlook.com</email>
    </contact>
    <investigator>
      <last_name>Lina Zhao, Ph.D</last_name>
      <role>Principal Investigator</role>
    </investigator>
    <investigator>
      <last_name>Mei Shi, MD</last_name>
      <role>Principal Investigator</role>
    </investigator>
  </location>
  <location_countries>
    <country>China</country>
  </location_countries>
  <verification_date>January 2017</verification_date>
  <study_first_submitted>January 5, 2017</study_first_submitted>
  <study_first_submitted_qc>January 20, 2017</study_first_submitted_qc>
  <study_first_posted type="Estimate">January 24, 2017</study_first_posted>
  <last_update_submitted>January 20, 2017</last_update_submitted>
  <last_update_submitted_qc>January 20, 2017</last_update_submitted_qc>
  <last_update_posted type="Estimate">January 24, 2017</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>Mei Shi</investigator_full_name>
    <investigator_title>Professor</investigator_title>
  </responsible_party>
  <keyword>Esophageal Cancer</keyword>
  <keyword>Prediction</keyword>
  <keyword>Biomarker</keyword>
  <keyword>MRI-DWI</keyword>
  <keyword>PET-CT</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Esophageal 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>


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/NCT03029793
org study id: XJFL-2016-ESO
nct id: NCT03029793
lead sponsor: 
has dmc: No
The purpose of this study is to determine whether combination of molecular and biomarkers
      with functional imaging can predict pathologic response and clinical outcomes in squamous
      esophageal cancer patients who undergo trimodality therapy which includes neoadjuvant
      chemoradiotherapy and surgery
The recommended care for the management of locally advanced esophageal cancers is neoadjuvant
      chemoradiotherapy (nCRT) followed by esophagectomy based on the NCCN guideline. The rate of
      pathologic complete response (pCR) after nCRT was around 25-30%, reflecting potential cure of
      unresectable esophageal cancer receiving CRT. Since esophagectomy might have substantial
      morbidity and mortality rate, establishing the model for predicting nCRT response and
      survival will guide neoadjuvant treatment decisions and personalized treatment. Thus surgery
      might be spared in some patients with complete responses after nCRT, and surgery could be
      selectively reserved for those with only partial or no response to CRT. However, reported
      models yield unsatisfactory results due to small sample size and low accuracy, and most cases
      were adenocarcinoma and few models were used to predict survival. This study will
      prospectively collect the tissue and blood samples of locally advanced esophageal cancer
      patients, detect CRT resistance biomarkers, assess the SUV value and texture parameters of
      18F-FDG PET-CT as well as ADC values DWI-MRI. The investigators will use advanced statistical
      tools to establish the model and further validate the model in another group of patients.The
      investigators will also establish a model for survival prediction. This model might possibly
      guide the personalized treatment for esophageal squamous cell carcinoma patients in China.
observational model: Cohort
time perspective: Prospective
measure: Pathologic Response
time frame: Approximately 12 months
description: Mandard tumor regression grade (TRG) was used for pathology analysis. Primary tumor and positive lymph node regression were classified into five histologic tumor regression grades. Grade 1 (complete regression) showed absence of histologically identifiable residual cancer and fibrosis extending through the different layers of the esophageal wall, with or without granuloma. Grade 2 was characterized by the presence of rare residual cancer cells scattered through the fibrosis. Grade 3 involved an increase in the number of residual cancer cells, but fibrosis still predominated. Grade 4 showed residual cancer outgrowing fibrosis. Grade 5 was characterized by the absence of regressive changes.
measure: Overall Survival
time frame: Approximately 4 years
arm group label: Biomarkers and Imaging analysis
description: This study will prospectively collect the tissue and blood samples of locally advanced esophageal cancer patients, perform CRT resistance biomarkers testing and functional imaging analysis including SUV value and texture parameters of 18F-FDG PET-CT as well as ADC values DWI-MRI before treatment, 2-3 weeks after the initiation of CRT, and 4 weeks post-nCRT. The investigators will use advanced statistical tools to establish the model and further validate the model in another group of patients. The investigators will also establish a model for survival prediction.
intervention type: Other
intervention name: Biomarkers Testing
description: CRT resistance biomarkers will be detected before CRT, 2-3 weeks after the initiation of CRT, and 4 weeks post-CRT.
arm group label: Biomarkers and Imaging analysis
intervention type: Other
intervention name: Functional Imaging analysis
description: The SUV value and texture parameters of 18F-FDG PET-CT as well as ADC values DWI-MRI will be measures before CRT, 2-3 weeks after the initiation of CRT, and 4 weeks post-CRT.
arm group label: Biomarkers and Imaging analysis
study pop: 
sampling method: Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: 70 Years
healthy volunteers: No
last name: Mei Shi, MD
role: Study Chair
affiliation: Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University
last name: Li-Na Zhao, MD, Ph.D
phone: +86-29-84775425
email: zhaolinazln@outlook.com
facility: 
status: Recruiting
contact: 
investigator: 
investigator: 
country: China
responsible party type: Principal Investigator
investigator affiliation: Air Force Military Medical University, China
investigator full name: Mei Shi
investigator title: Professor
mesh term: Esophageal Neoplasms
sharing ipd: No