Liver Transplant DisorderTRAIN-AINCT05200195
Deep Learning Model for the Prediction of Post-LT HCC Recurrence
An observational study of Liver Transplant Disorder and Liver Cancer, run by European Hepatocellular Cancer Liver Transplant Group at 1 site in Italy.
Trial summary
Identifying patients at high risk for recurrence of hepatocellular carcinoma (HCC) after liver transplantation (LT) represents a challenging issue. The present study aims to develop and validate an accurate post-LT recurrence prediction calculator using the machine learning method. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Liver Transplant Disorder, Liver Cancer, Recurrent Cancer
- What is being tested?
- Liver transplantation
- Type of treatment
- Surgery or procedure
- How many people
- 4,026 participants
- Where
- 1 siteItaly
- Study dates
- 15 Jan 2020to 15 Mar 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: All the consecutive adult (≥18 years) patients enlisted and transplanted with the primary diagnosis of HCC during the period 2000-2018 in the 18 centers composing the International and the Validation Cohorts
Who may be able to join
- Consecutive adult (≥18 years) patients enlisted and transplanted with the primary diagnosis of HCC during the period 2000-2018.
Who cannot join
- Patients with HCC diagnosed only at pathological examination (incidental HCC)
- Patients with mixed hepatocellular-cholangiocellular cancer misdiagnosed as HCC
- Patients with cholangiocellular cancer misdiagnosed as HCC
- Patients dying early after LT (≤ one month)
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Development and Validation of a Deep Learning Model for the Prediction of Hepatocellular Cancer Recurrence After Transplantation: The Time-Radiological Response- AlphafetoproteIN-Artificial Intelligence Model
Identifying patients at high risk for recurrence of hepatocellular carcinoma (HCC) after liver transplantation (LT) represents a challenging issue. The present study aims to develop and validate an accurate post-LT recurrence prediction calculator using the machine learning method.
Read the detailed description
In 1996, the introduction of the Milan criteria (MC) strongly modified the selection process of hepatocellular cancer (HCC) patients waiting for liver transplantation (LT). Many attempts to widen MC have been proposed. Initially, exclusively morphology-based (nodules number and target lesion diameter) criteria were created. In the last years, extended criteria also based on biological parameters have been added. Among the most adopted biology-based features, the levels of different tumor markers, liver function parameters like the model for end-stage liver disease (MELD), the radiological response after neo-adjuvant therapies, and the length of waiting-time (WT) can be reported.
Unfortunately, all the proposed models showed suboptimal prediction abilities for the risk of post-LT recurrence. Such impairment was derived from the limitations of the standard statistical methods to account for many variables and their non-linear interactions. Therefore, developing a model based on Artificial Intelligence (AI) represents an attractive way to improve prediction ability.
Thus, the investigators hypothesize that an AI model focused on an accurate post-transplant HCC recurrence prediction should improve our ability to pre-operatively identify patients with different classes of risk for HCC recurrence after transplant.
This study aims to develop an AI-derived prediction model combining morphology and biology variables. A Training Set derived from an International Cohort was adopted for doing this. A Test Set derived from the same International Cohort and a Validation Cohort were adopted for the internal and external validation, respectively. A user-friendly web calculator was also developed.
- Conditions
- Liver Transplant Disorder, Liver Cancer, Recurrent Cancer
- Being tested
- Liver transplantation
- Keywords
- artificial intelligence, deep learning, mathematical model
- Medical subject headings
- Liver Neoplasms, Recurrence
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Liver transplantationProcedure or surgery
Deceased or living donor liver transplantation for the cure of hepatocellular cancer on cirrhosis
| Study group | Role | What they receive |
|---|---|---|
| International Cohort Training Set | The Training Set of the International Cohort (N=3,670) was composed of the 80% (n=2936) HCC patients transplanted from 2000 to 2018 across 17 centers in Europe and Asia. Receives: Procedure: Liver transplantation | |
| International Cohort Test Set | The Test Set of the International Cohort (N=3,670) was composed of the 20% (n=734) HCC patients transplanted from 2000 to 2018 across 17 centers in Europe and Asia. Receives: Procedure: Liver transplantation | |
| Validation Cohort | The external Validation Cohort was composed of 356 HCC patients transplanted at the Columbia University, New York, during the period 2000-2018. Receives: Procedure: Liver transplantation |
What is being measured
The primary outcome is the main question the study is designed to answer.
Post-transplant HCC recurrence
Intra- and/or extrahepatic recidivism of HCC after liver transplantation
Measured: 5 years from liver transplantation
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted20 Jan 2022
- Study start15 Jan 2020
- Primary completion15 Dec 2021
- Study completion15 Mar 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Liver Transplant DisorderStudies of the same condition, open and under way.
- 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
- 4,026 participants (actual)
Sponsor and investigators
- Lead sponsor
- European Hepatocellular Cancer Liver Transplant Group
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Quirino Lai, European Hepatocellular Cancer Liver Transplant Group
- Investigators
- Quirino Lai, MD PhD, Principal investigator, University of Roma La Sapienza
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05200195
- Sponsor's protocol ID
- #004
- Acronym
- TRAIN-AI
- Status last verified
- Jun 2022
- First submitted
- 7 Jan 2022
- Last updated
- 30 Jun 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 30 Jun 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development and Validation of a Deep Learning Model for the Prediction of Hepatocellular Cancer Recurrence After Transplantation: The Time-Radiological Response- AlphafetoproteIN-Artificial Intelligence Model
- ClinicalTrials.gov ID
- NCT05200195
- Acronym / sponsor ID
- TRAIN-AI / #004
- Conditions
- Liver Transplant Disorder, Liver Cancer, Recurrent Cancer
- Keywords
- artificial intelligence, deep learning, mathematical model
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 4,026 participants (actual)
- Lead sponsor
- European Hepatocellular Cancer Liver Transplant GroupUniversity, hospital or other
- Study start
- 15 Jan 2020 (actual)
- Primary completion
- 15 Dec 2021 (actual)
- Study completion
- 15 Mar 2022 (actual)
- First posted
- 20 Jan 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.
Identifying patients at high risk for recurrence of hepatocellular carcinoma (HCC) after liver transplantation (LT) represents a challenging issue. The present study aims to develop and validate an accurate post-LT recurrence prediction calculator using the machine learning method.
Detailed description
In 1996, the introduction of the Milan criteria (MC) strongly modified the selection process of hepatocellular cancer (HCC) patients waiting for liver transplantation (LT). Many attempts to widen MC have been proposed. Initially, exclusively morphology-based (nodules number and target lesion diameter) criteria were created. In the last years, extended criteria also based on biological parameters have been added. Among the most adopted biology-based features, the levels of different tumor markers, liver function parameters like the model for end-stage liver disease (MELD), the radiological response after neo-adjuvant therapies, and the length of waiting-time (WT) can be reported.
Unfortunately, all the proposed models showed suboptimal prediction abilities for the risk of post-LT recurrence. Such impairment was derived from the limitations of the standard statistical methods to account for many variables and their non-linear interactions. Therefore, developing a model based on Artificial Intelligence (AI) represents an attractive way to improve prediction ability.
Thus, the investigators hypothesize that an AI model focused on an accurate post-transplant HCC recurrence prediction should improve our ability to pre-operatively identify patients with different classes of risk for HCC recurrence after transplant.
This study aims to develop an AI-derived prediction model combining morphology and biology variables. A Training Set derived from an International Cohort was adopted for doing this. A Test Set derived from the same International Cohort and a Validation Cohort were adopted for the internal and external validation, respectively. A user-friendly web calculator was also developed.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| International Cohort Training Set | – | Procedure: Liver transplantationThe Training Set of the International Cohort (N=3,670) was composed of the 80% (n=2936) HCC patients transplanted from 2000 to 2018 across 17 centers in Europe and Asia. |
| International Cohort Test Set | – | Procedure: Liver transplantationThe Test Set of the International Cohort (N=3,670) was composed of the 20% (n=734) HCC patients transplanted from 2000 to 2018 across 17 centers in Europe and Asia. |
| Validation Cohort | – | Procedure: Liver transplantationThe external Validation Cohort was composed of 356 HCC patients transplanted at the Columbia University, New York, during the period 2000-2018. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- All the consecutive adult (≥18 years) patients enlisted and transplanted with the primary diagnosis of HCC during the period 2000-2018 in the 18 centers composing the International and the Validation Cohorts
Key inclusion criteria (1 listed)
- Consecutive adult (≥18 years) patients enlisted and transplanted with the primary diagnosis of HCC during the period 2000-2018.
Key exclusion criteria (4 listed)
- Patients with HCC diagnosed only at pathological examination (incidental HCC)
- Patients with mixed hepatocellular-cholangiocellular cancer misdiagnosed as HCC
- Patients with cholangiocellular cancer misdiagnosed as HCC
- Patients dying early after LT (≤ one month)
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 |
|---|---|---|
| Liver transplantationDeceased or living donor liver transplantation for the cure of hepatocellular cancer on cirrhosis | Procedure or surgery | International Cohort Test Set, International Cohort Training Set, Validation Cohort |
Primary outcome
Post-transplant HCC recurrence
Time frame: 5 years from liver transplantation
Intra- and/or extrahepatic recidivism of HCC after liver transplantation
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 30 Jun 2022.
- Individual participant dataSharing planned: No
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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.
Quirino Lai, MD PhD principal investigator
University of Roma La Sapienza
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 Liver Transplant Disorder and Liver Cancer, run by European Hepatocellular Cancer Liver Transplant Group at 1 site in Italy.
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 1 inclusion and 4 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 30 Jun 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 Italy. 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?
Post-transplant HCC recurrence (time frame: 5 years from liver transplantation). 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 30 Jun 2022.