CT Scans Prior to Surgery With a Least 2 Years of Follow-upLIVERIBIOPSYNCT05235490
Identification of Image Phenotypes to Predict Recurrence After Resection of Hepatocellular Carcinoma
An observational study of CT Scans Prior to Surgery With a Least 2 Years of Follow-up, run by Assistance Publique - Hôpitaux de Paris at 1 site in France.
Trial summary
Tumor recurrence, which occurs in 70% of patients with HCC within 5 years after hepatic resection, is a major cause of post-resection-death. This recurrence can be true recurrence (intrahepatic metastases), which occurs sooner than 2 years later, or it can be due to the development of de-novo tumors at least 2 years… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- CT Scans Prior to Surgery With a Least 2 Years of Follow-up
- What is being tested?
- Non intervention
- How many people
- 100 participants
- Where
- 1 siteFrance
- Study dates
- 28 Jan 2021to 9 Feb 2022
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Data of patients who has hepatectomy (resection R0) for an HCC treatment will be collected from January 2011 to December 2019.
Who may be able to join
- Age ≥ 18 years old
- Patients who underwent surgery and have R0 resection after 2010
- Multiphase CT scans with contrast media should be performed within 2 months prior to surgical intervention
- At least 2 years of follow-up data on intrahepatic recurrence
Who cannot join
- Previous HCC treatment
- Combination of other anti-cancer treatment
- Other malignancies
- Patient expressly expressing opposition to the exploitation of their data as defined by the project
- Protected adults
Trial locations and contacts
1 site in 1 country.
About this study
Tumor recurrence, which occurs in 70% of patients with HCC within 5 years after hepatic resection, is a major cause of post-resection-death. This recurrence can be true recurrence (intrahepatic metastases), which occurs sooner than 2 years later, or it can be due to the development of de-novo tumors at least 2 years later. Despite this high rate of tumor recurrence, no anti-recurrence adjuvant therapies are currently recommended.
Imaging phenomics is the systematic, large scale extraction of imaging features for the characterization and classification of disease phenotypes. Combining imaging and tissue phenomics could be a solution to predict HCC recurrence. With the emergence of molecular therapies and immunotherapies, identifying patients with HCC at high risk of post-resection recurrence would help determine additional therapeutic and management strategies in clinical practice.
Read the detailed description
Hepatocellular carcinoma (HCC) is among the most lethal and prevalent cancers in the human population and it is now the third leading cause of cancer deaths worldwide, with over 500,000 people affected. Because of the high recurrence rate after curative hepatectomy, accurate prognostic assessment in HCC patients are quite important. With the emergence of molecular therapies and immunotherapies, the identification of patients at high or low risk for recurrence after hepatic resection would help determine additional therapeutic and management strategies in clinical practice. Although many immunohistochemical markers have been reported to have a prognostic value for HCC patients, there is no consensus on how these markers could add prognostic value to the clinical parameters.
In the initial step of biomarker discovery, no specific sample size is provided, however to test hypothesis, 100 patients are required.
This first study will potentially be followed by a second similar study promoted by the same investigators to increase the statistical power to improve the classification tool according to the patient's future.
Period covered by the data collection: 2011-2019 / Duration data collection: 1 year.
The primary endpoint will be built using machine learning method to obtain prediction of recurrence within 2 years. The Recurrence Free survival (RFS) within two years will be the reference outcome to evaluate the prognostic of the patients.
The secondary endpoint are following :
- A secondary endpoint which will be built using machine learning method to obtain prediction of recurrence after 2 years.
The Recurrence Free survival (RFS) after two years will be the reference outcome to evaluate the prognostic of the patients.
- A secondary endpoint will be the correlation between biomarker from CT scan and pathological biomarkers As the spectrum of HCC disease is very large, many patients to conduct conclusive validation studies for diagnostic and prognostic relevance need to be obtained.
Overall, each specific-read out endpoint will include a sample size calculation and - if appropriate - a power analysis specific to the objective of this study.
During training, phenotyping system performance assessment will be done to guide the calculation of the sample size for the validation.
- Being tested
- Non intervention
- Keywords
- Hepatocellular Carcinoma, Hepatic resection, Biomarkers from CT scan, Prognostic value, Early recurrence with hepatocellular cancer patients
- Medical subject headings
- Carcinoma, Hepatocellular
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Non interventionOther
Data study with inclusion of patients and retrospective clinical data collection, combining :
- Proofreading by radiologist of the CT scan performed (within 2 months prior to surgical intervention)
- Proofreading by iBiopsy® of the CT scan performed (within 2 months prior to surgical intervention)
- Proofreading of tumor sample slides by pathologists
- Patients follow-up (imaging, clinical)
- Recurrence-free survival
What is being measured
The primary outcome is the main question the study is designed to answer.
The main objective of this work is to identify biomarkers from CT scan (non-invasive imaging phenotypes from radiological images) which have a prognostic value for an early recurrence in patients with hepatocellular cancer.
The primary endpoint will be built using machine learning method to obtain prediction of recurrence within 2 years. The Recurrence Free survival (RFS) within two years will be the reference outcome to evaluate the prognostic of the patients.
Measured: 2 years
Secondary outcomes (1)
Identify biomarkers from CT scan (non-invasive imaging phenotypes from radiological images) which have a prognostic value for a tardive recurrence in patients with hepatocellular cancer.
A secondary endpoint which will be built using machine learning method to obtain prediction of recurrence after 2 years. The Recurrence Free survival (RFS) after two years will be the reference outcome to evaluate the prognostic of the patients.
Measured: 2 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 Feb 2022
- Study start28 Jan 2021
- Primary completion28 Jan 2022
- Study completion9 Feb 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for CT Scans Prior to Surgery With a Least 2 Years of Follow-upStudies of the same condition, open and under way.
- More trials run by Assistance Publique - Hôpitaux de ParisThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 100 participants (actual)
Sponsor and investigators
- Lead sponsor
- Assistance Publique - Hôpitaux de Paris
- Sponsor type
- University, hospital or other
- Collaborators
- Median Technologies
- Responsible party
- Sponsor
- Investigators
- Maïté LEWIN, Professor, Principal investigator, Paul Brousse Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05235490
- Sponsor's protocol ID
- APHP191113
- Acronym
- LIVERIBIOPSY
- Status last verified
- Feb 2022
- First submitted
- 20 Dec 2021
- Last updated
- 11 Feb 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 11 Feb 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Identification of Image Phenotypes to Predict Recurrence After Resection of Hepatocellular Carcinoma
- ClinicalTrials.gov ID
- NCT05235490
- Acronym / sponsor ID
- LIVERIBIOPSY / APHP191113
- Keywords
- Hepatocellular Carcinoma, Hepatic resection, Biomarkers from CT scan, Prognostic value, Early recurrence with hepatocellular cancer patients
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 100 participants (actual)
- Lead sponsor
- Assistance Publique - Hôpitaux de ParisUniversity, hospital or other
- Collaborators
- Median Technologies
- Study start
- 28 Jan 2021 (actual)
- Primary completion
- 28 Jan 2022 (actual)
- Study completion
- 9 Feb 2022 (actual)
- First posted
- 11 Feb 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Tumor recurrence, which occurs in 70% of patients with HCC within 5 years after hepatic resection, is a major cause of post-resection-death. This recurrence can be true recurrence (intrahepatic metastases), which occurs sooner than 2 years later, or it can be due to the development of de-novo tumors at least 2 years later. Despite this high rate of tumor recurrence, no anti-recurrence adjuvant therapies are currently recommended.
Imaging phenomics is the systematic, large scale extraction of imaging features for the characterization and classification of disease phenotypes. Combining imaging and tissue phenomics could be a solution to predict HCC recurrence. With the emergence of molecular therapies and immunotherapies, identifying patients with HCC at high risk of post-resection recurrence would help determine additional therapeutic and management strategies in clinical practice.
Detailed description
Hepatocellular carcinoma (HCC) is among the most lethal and prevalent cancers in the human population and it is now the third leading cause of cancer deaths worldwide, with over 500,000 people affected. Because of the high recurrence rate after curative hepatectomy, accurate prognostic assessment in HCC patients are quite important. With the emergence of molecular therapies and immunotherapies, the identification of patients at high or low risk for recurrence after hepatic resection would help determine additional therapeutic and management strategies in clinical practice. Although many immunohistochemical markers have been reported to have a prognostic value for HCC patients, there is no consensus on how these markers could add prognostic value to the clinical parameters.
In the initial step of biomarker discovery, no specific sample size is provided, however to test hypothesis, 100 patients are required.
This first study will potentially be followed by a second similar study promoted by the same investigators to increase the statistical power to improve the classification tool according to the patient's future.
Period covered by the data collection: 2011-2019 / Duration data collection: 1 year.
The primary endpoint will be built using machine learning method to obtain prediction of recurrence within 2 years. The Recurrence Free survival (RFS) within two years will be the reference outcome to evaluate the prognostic of the patients.
The secondary endpoint are following :
- A secondary endpoint which will be built using machine learning method to obtain prediction of recurrence after 2 years.
The Recurrence Free survival (RFS) after two years will be the reference outcome to evaluate the prognostic of the patients.
- A secondary endpoint will be the correlation between biomarker from CT scan and pathological biomarkers As the spectrum of HCC disease is very large, many patients to conduct conclusive validation studies for diagnostic and prognostic relevance need to be obtained.
Overall, each specific-read out endpoint will include a sample size calculation and - if appropriate - a power analysis specific to the objective of this study.
During training, phenotyping system performance assessment will be done to guide the calculation of the sample size for the validation.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Data of patients who has hepatectomy (resection R0) for an HCC treatment will be collected from January 2011 to December 2019.
Key inclusion criteria (4 listed)
- Age ≥ 18 years old
- Patients who underwent surgery and have R0 resection after 2010
- Multiphase CT scans with contrast media should be performed within 2 months prior to surgical intervention
- At least 2 years of follow-up data on intrahepatic recurrence
Key exclusion criteria (5 listed)
- Previous HCC treatment
- Combination of other anti-cancer treatment
- Other malignancies
- Patient expressly expressing opposition to the exploitation of their data as defined by the project
- Protected adults
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Non interventionData study with inclusion of patients and retrospective clinical data collection, combining : * Proofreading by radiologist of the CT scan performed (within 2 months prior to surgical intervention) * Proofreading by iBiopsy® of the CT scan performed (within 2 months prior to surgical intervention) * Proofreading of tumor sample slides by pathologists * Patients follow-up (imaging, clinical) * Recurrence-free survival | Other | – |
Primary outcome
The main objective of this work is to identify biomarkers from CT scan (non-invasive imaging phenotypes from radiological images) which have a prognostic value for an early recurrence in patients with hepatocellular cancer.
Time frame: 2 years
The primary endpoint will be built using machine learning method to obtain prediction of recurrence within 2 years. The Recurrence Free survival (RFS) within two years will be the reference outcome to evaluate the prognostic of the patients.
1 secondary outcome
Identify biomarkers from CT scan (non-invasive imaging phenotypes from radiological images) which have a prognostic value for a tardive recurrence in patients with hepatocellular cancer.
Time frame: 2 years
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 11 Feb 2022.
- Individual participant dataSharing planned: No
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Maïté LEWIN, Professor principal investigator
Paul Brousse Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of CT Scans Prior to Surgery With a Least 2 Years of Follow-up, run by Assistance Publique - Hôpitaux de Paris at 1 site in France.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 11 Feb 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in France. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The main objective of this work is to identify biomarkers from CT scan (non-invasive imaging phenotypes from radiological images) which have a prognostic value for an early recurrence in patients with hepatocellular cancer. (time frame: 2 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 11 Feb 2022.