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/NCT05976113</url>
    </required_header>
    <id_info>
      <org_study_id>1402020</org_study_id>
      <nct_id>NCT05976113</nct_id>
    </id_info>
    <brief_title>A Retrospective Study on Multiple Classifier Endometrial Cancer</brief_title>
    <official_title>Multiple Classifier Endometrial Cancer</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Fondazione IRCCS Istituto Nazionale dei Tumori, Milano</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
    </sponsors>
    <source>Fondazione IRCCS Istituto Nazionale dei Tumori, Milano</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>
        Endometrial cancer is not a single entity but rather a very heterogeneous group of diseases.&#xD;
        Historically, endometrial cancer patients have been classified as endometrioid (type I) or&#xD;
        non-endometrioid (type II) according to the dualistic Bokhman model- However, this approach&#xD;
        has been limited in accurately predicting prognosis and guiding treatment owing to&#xD;
        heterogeneity within subtypes, inadequate incorporation of molecular and genetic information,&#xD;
        and high interobserver variability .&#xD;
  &#xD;
        In the last ten years, after the publication of The Cancer Genome Atlas (TCGA)[5], the&#xD;
        molecular classification of endometrial cancer into four molecular subtypes [(i)&#xD;
        POLE/ultramutated group (POLE mutated), (ii) mismatch repair&#xD;
        deficiency/microsatellite-instable, hypermutated group (MMRd/MSI-H), (iii) copy-number-high,&#xD;
        TP53-mutant (CNH/p53abn), and (iv) copy-number-low, TP53-wild-type (CNL, or No Specific&#xD;
        Mutational Profile [NSMP])] has rapidly gained interest. Recently, the European Societies of&#xD;
        Gynaecological Oncology, Radiotherapy and Oncology, and Pathology (ESGO-ESTRO-ESP), the&#xD;
        European Society of Medical Oncology (ESMO), the National Comprehensive Cancer Network&#xD;
        (NCCN), and the new 2023 International Federation of Gynecology and Obstetrics (FIGO) staging&#xD;
        system have promoted the use of (surrogate) molecular classification. Retrospective studies&#xD;
        supported the value of adopting molecular classification to offer reliable data on&#xD;
        prognostication and adjuvant treatment decisions. Although no prospective data are available,&#xD;
        current guidelines promote the use of molecular profiles to tailor adjuvant treatment after&#xD;
        surgery. As only a few retrospective studies have investigated the association between&#xD;
        molecular profiles and response to various adjuvant treatments, it is important to note that&#xD;
        data are limited. Interestingly, the growing adoption of molecular profiling led to the&#xD;
        detection of a subgroup of tumors called multiple classifiers, characterized by multiple (two&#xD;
        or three) molecular features. According to the guidelines, tumors with a POLE mutation should&#xD;
        be considered POLEmut, regardless of other molecular features, whereas MMRd/MSI-H tumors with&#xD;
        a p53 abnormality should be considered MMRd/MSI-H. Data on these patients is limited and&#xD;
        fragmentary. The aforementioned consensus is based solely on a large retrospective cohort of&#xD;
        multiple classifiers collected by Leon-Castillo et al.. Hence, to fill this literature gap,&#xD;
        the investigators designed this retrospective study, which aimed to collect multiple&#xD;
        classifiers patients to improve knowledge on this emerging category.&#xD;
      </textblock>
    </brief_summary>
    <overall_status>Recruiting</overall_status>
    <start_date type="Actual">July 27, 2023</start_date>
    <completion_date type="Anticipated">August 31, 2023</completion_date>
    <primary_completion_date type="Anticipated">August 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>progression-free survival</measure>
      <time_frame>24 months</time_frame>
    </primary_outcome>
    <number_of_groups>1</number_of_groups>
    <enrollment type="Anticipated">80</enrollment>
    <condition>Uterine Cancer</condition>
    <arm_group>
      <arm_group_label>Patients with multiple classifier endometrial cancer</arm_group_label>
      <description>Endometrial cancer patients who have two or more molecular features</description>
    </arm_group>
    <intervention>
      <intervention_type>Other</intervention_type>
      <intervention_name>Observation only</intervention_name>
      <description>Just obsrevation following standard of care (including surgery, chemotherapy and radiation when appropriate)</description>
      <arm_group_label>Patients with multiple classifier endometrial cancer</arm_group_label>
    </intervention>
    <eligibility>
      <study_pop>
        <textblock>
          This is a retrospective study with patients diagnosed with multiple classifier endometrial&#xD;
          cancer Data of consecutive patients treated between June 1, 2019, and January 31, 2023,&#xD;
          were collected.&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Non-Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion criteria were the following: (i) histological diagnosis of endometrial cancer;&#xD;
          (ii) execution of hysterectomy (with or without salpingo-oophorectomy) with or without&#xD;
          nodal dissection; (iii) apparent early-stage disease; (iv) conventional pathological&#xD;
          evaluation; and (v) molecular/genomic evaluation of the disease (including at least POLE&#xD;
          sequencing, MMR protein immunostaining or MSI assessment, p53 immunostaining or TP53&#xD;
          sequencing). Exclusion criteria were: (i) consent withdrawal, (ii) execution of neoadjuvant&#xD;
          therapy, and (iii) stage IV disease.&#xD;
        </textblock>
      </criteria>
      <gender>Female</gender>
      <gender_based>Yes</gender_based>
      <gender_description>patients with uterine cancers</gender_description>
      <minimum_age>18 Years</minimum_age>
      <maximum_age>N/A</maximum_age>
      <healthy_volunteers>No</healthy_volunteers>
    </eligibility>
    <location>
      <facility>
        <name>Fondazione IRCCS Istituto Nazionale dei Tumori di Milano</name>
        <address>
          <city>Milan</city>
          <zip>20133</zip>
          <country>Italy</country>
        </address>
      </facility>
      <status>Recruiting</status>
      <contact>
        <last_name>Giorgio Bogani</last_name>
        <phone>3803933116</phone>
        <email>giorgiobogani@yahoo.it</email>
      </contact>
    </location>
    <location_countries>
      <country>Italy</country>
    </location_countries>
    <verification_date>July 2023</verification_date>
    <study_first_submitted>July 27, 2023</study_first_submitted>
    <study_first_submitted_qc>July 27, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 4, 2023</study_first_posted>
    <last_update_submitted>July 27, 2023</last_update_submitted>
    <last_update_submitted_qc>July 27, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 4, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Endometrial Neoplasms</mesh_term>
      <mesh_term>Uterine Neoplasms</mesh_term>
    </condition_browse>
    <patient_data>
      <sharing_ipd>Undecided</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/NCT05976113
  org study id: 1402020
  nct id: NCT05976113
  lead sponsor: 
  is fda regulated drug: No
  is fda regulated device: No
  Endometrial cancer is not a single entity but rather a very heterogeneous group of diseases.
        Historically, endometrial cancer patients have been classified as endometrioid (type I) or
        non-endometrioid (type II) according to the dualistic Bokhman model- However, this approach
        has been limited in accurately predicting prognosis and guiding treatment owing to
        heterogeneity within subtypes, inadequate incorporation of molecular and genetic information,
        and high interobserver variability .
  
        In the last ten years, after the publication of The Cancer Genome Atlas (TCGA)[5], the
        molecular classification of endometrial cancer into four molecular subtypes [(i)
        POLE/ultramutated group (POLE mutated), (ii) mismatch repair
        deficiency/microsatellite-instable, hypermutated group (MMRd/MSI-H), (iii) copy-number-high,
        TP53-mutant (CNH/p53abn), and (iv) copy-number-low, TP53-wild-type (CNL, or No Specific
        Mutational Profile [NSMP])] has rapidly gained interest. Recently, the European Societies of
        Gynaecological Oncology, Radiotherapy and Oncology, and Pathology (ESGO-ESTRO-ESP), the
        European Society of Medical Oncology (ESMO), the National Comprehensive Cancer Network
        (NCCN), and the new 2023 International Federation of Gynecology and Obstetrics (FIGO) staging
        system have promoted the use of (surrogate) molecular classification. Retrospective studies
        supported the value of adopting molecular classification to offer reliable data on
        prognostication and adjuvant treatment decisions. Although no prospective data are available,
        current guidelines promote the use of molecular profiles to tailor adjuvant treatment after
        surgery. As only a few retrospective studies have investigated the association between
        molecular profiles and response to various adjuvant treatments, it is important to note that
        data are limited. Interestingly, the growing adoption of molecular profiling led to the
        detection of a subgroup of tumors called multiple classifiers, characterized by multiple (two
        or three) molecular features. According to the guidelines, tumors with a POLE mutation should
        be considered POLEmut, regardless of other molecular features, whereas MMRd/MSI-H tumors with
        a p53 abnormality should be considered MMRd/MSI-H. Data on these patients is limited and
        fragmentary. The aforementioned consensus is based solely on a large retrospective cohort of
        multiple classifiers collected by Leon-Castillo et al.. Hence, to fill this literature gap,
        the investigators designed this retrospective study, which aimed to collect multiple
        classifiers patients to improve knowledge on this emerging category.
  observational model: Cohort
  time perspective: Retrospective
  measure: progression-free survival
  time frame: 24 months
  arm group label: Patients with multiple classifier endometrial cancer
  description: Endometrial cancer patients who have two or more molecular features
  intervention type: Other
  intervention name: Observation only
  description: Just obsrevation following standard of care (including surgery, chemotherapy and radiation when appropriate)
  arm group label: Patients with multiple classifier endometrial cancer
  study pop: 
  sampling method: Non-Probability Sample
  criteria: 
  gender: Female
  gender based: Yes
  gender description: patients with uterine cancers
  minimum age: 18 Years
  maximum age: N/A
  healthy volunteers: No
  facility: 
  status: Recruiting
  contact: 
  country: Italy
  responsible party type: Sponsor
  mesh term: Endometrial Neoplasms
  mesh term: Uterine Neoplasms
  sharing ipd: Undecided