<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/NCT03294434</url>
  </required_header>
  <id_info>
    <org_study_id>PRaM-GBM</org_study_id>
    <nct_id>NCT03294434</nct_id>
  </id_info>
  <brief_title>Predicting Sites of Tumour Progression in the Invasive Margin of Glioblastomas (PRaM-GBM Study)</brief_title>
  <acronym>PRaM-GBM</acronym>
  <official_title>Predicting Sites of Tumour Progression in the Invasive Margin of Glioblastomas (PRaM-GBM Study)</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>CCTU- Cancer Theme</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Cambridge University Hospitals NHS Foundation Trust</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Cancer Research UK</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Experimental Cancer Medicine Centres</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Cambridge University Hospitals NHS Foundation Trust</source>
  <oversight_info>
    <has_dmc>No</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>
      Brain tumours are the leading cause of cancer deaths in children, men under the age of 45 and&#xD;
      women under the age of 25. Glioblastoma is the most common and most malignant primary tumour.&#xD;
      The predominant treatment is surgical removal of the tumour followed by radiotherapy. Sadly&#xD;
      the majority of patients given this treatment develop recurrent and progressive disease.&#xD;
&#xD;
      Better understanding of the invasive margin might improve outcomes by facilitating more&#xD;
      complete surgical resection beyond the traditional contrast enhancing margins. Diffusion&#xD;
      tensor MRI (DTI) is an imaging technique which may be able to predict the site of tumour&#xD;
      recurrence. DTI has previously been shown to identify regions, which have been confirmed with&#xD;
      biopsies, to be areas of invasive tumours and are present before progression is seen with an&#xD;
      MRI.&#xD;
&#xD;
      The primary aim of this study is to qualify an imaging biomarker that can be applied at&#xD;
      initial presentation, that can accurately predict the site of where glioblastomas will&#xD;
      progress after treatment and allow personalisation of both radiotherapy and surgical targets.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      This is a multicentre, prospective longitudinal observational cohort study in patients with&#xD;
      high grade glioma, who have surgery planned to remove &gt;90% of the tumour, and subsequent&#xD;
      radical radiotherapy with concomitant tomozolomide. The purpose of this study is to establish&#xD;
      a model using DTI that can accurately predict the site of where glioblastomas will progress&#xD;
      after treatment. This study aims to validate the use of DTI as a biomarker across multiple&#xD;
      centres to develop analysis methods that could be used in the future to personalise&#xD;
      radiotherapy treatment volumes, and potentially surgical targets.&#xD;
&#xD;
      Patients will be given a DTI-MRI both prior to the operation and prior to radiotherapy.&#xD;
      Clinical MRIs will take place according to standard guidelines. Whilst the study is open&#xD;
      patients will participate in the study until death. Once a total of 70 patients from the&#xD;
      first 90 have shown true progression patients will participate in the study for a minimum of&#xD;
      6 months from the beginning of radiotherapy.&#xD;
&#xD;
      This study will be conducted in 6-10 NHS centres, where 120 patients will be recruited,&#xD;
      patients who are withdrawn will be replaced.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Active, not recruiting</overall_status>
  <start_date type="Actual">March 2, 2017</start_date>
  <completion_date type="Anticipated">September 30, 2022</completion_date>
  <primary_completion_date type="Anticipated">June 30, 2022</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>Site of glioblastoma true progression correctly predicted by DTI scan</measure>
    <time_frame>18 months</time_frame>
    <description>Assess the diagnostic accuracy of DTI at pre-surgery or/and pre-radiotherapy as a biomarker to predict site of glioblastoma progression</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Accuracy of DTI as a biomarker</measure>
    <time_frame>18 months</time_frame>
    <description>Explore difference of DTI performed pre-surgery and pre-radiotherapy to predict the site of glioblastoma progression</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Perfusion imaging</measure>
    <time_frame>18 months</time_frame>
    <description>Investigate dynamic susceptibility imaging to measure rCBV of the invasive margin to improve the accuracy of the DTI biomarker.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Time to progression</measure>
    <time_frame>18 months</time_frame>
    <description>Investigate if pattern of invasion can predict time to progression</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Extent of resection and volume of tumour that remains post-surgery by standard imaging and DTI</measure>
    <time_frame>18 months</time_frame>
    <description>Determine the effect of resection on the invasive margin as determined by DTI</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Radiotherapy dose according to DTI-defined invasive region</measure>
    <time_frame>18 months</time_frame>
    <description>Retrospectively compare dose of radiotherapy using the DTI-defined invasive region receives with conventional radiotherapy plans</description>
  </secondary_outcome>
  <other_outcome>
    <measure>Difference of area highlighted by amino-acid PET and DTI-MRI</measure>
    <time_frame>18 months</time_frame>
    <description>Investigate the relationship between amino-acid PET, area of surgical resection and the area highlighted by DTI-MRI</description>
  </other_outcome>
  <other_outcome>
    <measure>Number of amino-acid PET only image guided biopsies taken from patients</measure>
    <time_frame>18 months</time_frame>
    <description>Investigate the feasibility of taking image-guided biopsies from patients in the region outside of the area with increased amino-acid PET uptake</description>
  </other_outcome>
  <other_outcome>
    <measure>Site of glioblastoma true progression correctly predicted from pre-operative imaging by a region that is predicted by the DTI abnormality outside of the area of increased uptake to amino-acid on PET</measure>
    <time_frame>18 months</time_frame>
    <description>Explore the extent of invasive disease (from DTI/perfusion) that is likely to be left following surgery by assessing potential resected tumour using amino acid PET</description>
  </other_outcome>
  <number_of_groups>1</number_of_groups>
  <enrollment type="Actual">139</enrollment>
  <condition>High Grade Glioma</condition>
  <arm_group>
    <arm_group_label>High Grade Glioma</arm_group_label>
    <description>Diffusion tensor Imaging (DTI-MRI) scan to be performed pre-operatively and pre-radiotherapy</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Diffusion tensor Imaging (DTI)</intervention_name>
    <description>Diffusion tensor Imaging (DTI) is a technique sensitive to the ordered diffusion of water along white matter tracts and can detect subtle disruption. A diffusion tensor signature method was developed that splits the tensor information into isotropic and anisotropic diffusion components. This can differentiate regions of pure tumour from invaded white matter.</description>
    <arm_group_label>High Grade Glioma</arm_group_label>
  </intervention>
  <biospec_retention>Samples With DNA</biospec_retention>
  <biospec_descr>
    <textblock>
      Patients that consent to participate in the optional PET sub-study will consent to the&#xD;
      collection of additional tissue biopsies to be taken at the time of their standard of care&#xD;
      surgery.&#xD;
    </textblock>
  </biospec_descr>
  <eligibility>
    <study_pop>
      <textblock>
        Male and female patients aged 16 and over with newly diagnosed glioblastomas&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Have given written informed consent to participate&#xD;
&#xD;
          -  Assessed by a neuroscience MDT to have a high grade glioma on imaging, OR if in the&#xD;
             opinion of the CI, with guidance from the local PI that all relevant and appropriate&#xD;
             members of a multidisciplinary team agree a high grade glioma diagnosis;&#xD;
&#xD;
          -  Considered suitable for radical radiotherapy (60 Gy) with concomitant chemotherapy&#xD;
             (Stupp Regime);&#xD;
&#xD;
          -  WHO PS 0 or 1 (see Appendix 3);&#xD;
&#xD;
          -  Age ≥16;&#xD;
&#xD;
          -  Patient suitable for tumour resection where the treating neurosurgeon feels that &gt;90%&#xD;
             of the enhancing tumour will be resected;&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Patients who are participating in trials involving investigational treatments&#xD;
&#xD;
          -  Patients who are unsuitable for a contrast-enhanced MRI will be excluded. Such&#xD;
             clinical problems include, but are not limited to:&#xD;
&#xD;
          -  MR unsafe metallic implants;&#xD;
&#xD;
          -  Claustrophobia;&#xD;
&#xD;
          -  Allergy to gadolinium contrast agent;&#xD;
&#xD;
          -  History of severe renal impairment.&#xD;
&#xD;
          -  Patients unable to provide written informed consent&#xD;
&#xD;
          -  PET sub-study only: Pregnant women&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>16 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Stephen Price</last_name>
    <role>Principal Investigator</role>
    <affiliation>Cambridge University Hospitals NHS Foundation Trust</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Cambridge University Hospitals NHS Foundation Trust</name>
      <address>
        <city>Cambridge</city>
        <zip>CB2 0QQ</zip>
        <country>United Kingdom</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United Kingdom</country>
  </location_countries>
  <verification_date>December 2021</verification_date>
  <study_first_submitted>September 22, 2017</study_first_submitted>
  <study_first_submitted_qc>September 22, 2017</study_first_submitted_qc>
  <study_first_posted type="Actual">September 27, 2017</study_first_posted>
  <last_update_submitted>December 29, 2021</last_update_submitted>
  <last_update_submitted_qc>December 29, 2021</last_update_submitted_qc>
  <last_update_posted type="Actual">January 11, 2022</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor-Investigator</responsible_party_type>
    <investigator_affiliation>Cambridge University Hospitals NHS Foundation Trust</investigator_affiliation>
    <investigator_full_name>CCTU- Cancer Theme</investigator_full_name>
    <investigator_title>CCTU-Cancer Theme</investigator_title>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Glioblastoma</mesh_term>
  </condition_browse>
  <!-- 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/NCT03294434
org study id: PRaM-GBM
nct id: NCT03294434
lead sponsor: 
collaborator: 
collaborator: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
Brain tumours are the leading cause of cancer deaths in children, men under the age of 45 and
      women under the age of 25. Glioblastoma is the most common and most malignant primary tumour.
      The predominant treatment is surgical removal of the tumour followed by radiotherapy. Sadly
      the majority of patients given this treatment develop recurrent and progressive disease.

      Better understanding of the invasive margin might improve outcomes by facilitating more
      complete surgical resection beyond the traditional contrast enhancing margins. Diffusion
      tensor MRI (DTI) is an imaging technique which may be able to predict the site of tumour
      recurrence. DTI has previously been shown to identify regions, which have been confirmed with
      biopsies, to be areas of invasive tumours and are present before progression is seen with an
      MRI.

      The primary aim of this study is to qualify an imaging biomarker that can be applied at
      initial presentation, that can accurately predict the site of where glioblastomas will
      progress after treatment and allow personalisation of both radiotherapy and surgical targets.
This is a multicentre, prospective longitudinal observational cohort study in patients with
      high grade glioma, who have surgery planned to remove >90% of the tumour, and subsequent
      radical radiotherapy with concomitant tomozolomide. The purpose of this study is to establish
      a model using DTI that can accurately predict the site of where glioblastomas will progress
      after treatment. This study aims to validate the use of DTI as a biomarker across multiple
      centres to develop analysis methods that could be used in the future to personalise
      radiotherapy treatment volumes, and potentially surgical targets.

      Patients will be given a DTI-MRI both prior to the operation and prior to radiotherapy.
      Clinical MRIs will take place according to standard guidelines. Whilst the study is open
      patients will participate in the study until death. Once a total of 70 patients from the
      first 90 have shown true progression patients will participate in the study for a minimum of
      6 months from the beginning of radiotherapy.

      This study will be conducted in 6-10 NHS centres, where 120 patients will be recruited,
      patients who are withdrawn will be replaced.
observational model: Cohort
time perspective: Prospective
measure: Site of glioblastoma true progression correctly predicted by DTI scan
time frame: 18 months
description: Assess the diagnostic accuracy of DTI at pre-surgery or/and pre-radiotherapy as a biomarker to predict site of glioblastoma progression
measure: Accuracy of DTI as a biomarker
time frame: 18 months
description: Explore difference of DTI performed pre-surgery and pre-radiotherapy to predict the site of glioblastoma progression
measure: Perfusion imaging
time frame: 18 months
description: Investigate dynamic susceptibility imaging to measure rCBV of the invasive margin to improve the accuracy of the DTI biomarker.
measure: Time to progression
time frame: 18 months
description: Investigate if pattern of invasion can predict time to progression
measure: Extent of resection and volume of tumour that remains post-surgery by standard imaging and DTI
time frame: 18 months
description: Determine the effect of resection on the invasive margin as determined by DTI
measure: Radiotherapy dose according to DTI-defined invasive region
time frame: 18 months
description: Retrospectively compare dose of radiotherapy using the DTI-defined invasive region receives with conventional radiotherapy plans
measure: Difference of area highlighted by amino-acid PET and DTI-MRI
time frame: 18 months
description: Investigate the relationship between amino-acid PET, area of surgical resection and the area highlighted by DTI-MRI
measure: Number of amino-acid PET only image guided biopsies taken from patients
time frame: 18 months
description: Investigate the feasibility of taking image-guided biopsies from patients in the region outside of the area with increased amino-acid PET uptake
measure: Site of glioblastoma true progression correctly predicted from pre-operative imaging by a region that is predicted by the DTI abnormality outside of the area of increased uptake to amino-acid on PET
time frame: 18 months
description: Explore the extent of invasive disease (from DTI/perfusion) that is likely to be left following surgery by assessing potential resected tumour using amino acid PET
arm group label: High Grade Glioma
description: Diffusion tensor Imaging (DTI-MRI) scan to be performed pre-operatively and pre-radiotherapy
intervention type: Other
intervention name: Diffusion tensor Imaging (DTI)
description: Diffusion tensor Imaging (DTI) is a technique sensitive to the ordered diffusion of water along white matter tracts and can detect subtle disruption. A diffusion tensor signature method was developed that splits the tensor information into isotropic and anisotropic diffusion components. This can differentiate regions of pure tumour from invaded white matter.
arm group label: High Grade Glioma
Patients that consent to participate in the optional PET sub-study will consent to the
      collection of additional tissue biopsies to be taken at the time of their standard of care
      surgery.
study pop: 
sampling method: Probability Sample
criteria: 
gender: All
minimum age: 16 Years
maximum age: N/A
healthy volunteers: No
last name: Stephen Price
role: Principal Investigator
affiliation: Cambridge University Hospitals NHS Foundation Trust
facility: 
country: United Kingdom
responsible party type: Sponsor-Investigator
investigator affiliation: Cambridge University Hospitals NHS Foundation Trust
investigator full name: CCTU- Cancer Theme
investigator title: CCTU-Cancer Theme
mesh term: Glioblastoma