HCC - Hepatocellular CarcinomaNCT07444905
Prospective Evaluation of a Locked Risk-Stratified Surveillance Strategy for Extrahepatic Metastasis in Hepatocellular Carcinoma
An observational study of HCC - Hepatocellular Carcinoma and Machine Learning, run by Tongji Hospital at 1 site in China.
Trial summary
This is a multicenter prospective observational cohort study in adults with hepatocellular carcinoma (HCC) without baseline extrahepatic metastasis who are receiving routine clinical management and follow-up at participating centers. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- HCC - Hepatocellular Carcinoma, Machine Learning, Evaluation
- What is being tested?
- Machine Learning-Based Risk Assessment
- How many people
- 1,523 participants
- Where
- 1 siteChina
- Study dates
- 1 Feb 2022to 31 Dec 2026
- How long will I take part?
- 36 Months
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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: Adult patients with hepatocellular carcinoma (HCC) without evidence of extrahepatic metastasis at baseline who are receiving standard-of-care management and undergoing prospective follow-up in routine clinical practice. Participants are enrolled in a prospective observational cohort to evaluate a machine learning-based risk assessment strategy for predicting extrahepatic metastasis and supporting risk-adapted surveillance.
Who may be able to join
- Age ≥ 18 years.
- Diagnosis of hepatocellular carcinoma (HCC) confirmed by histopathology or accepted radiologic criteria per international guidelines.
- No evidence of extrahepatic metastasis at baseline evaluation.
- Receiving standard-of-care management with planned longitudinal follow-up in routine clinical practice.
- Availability of baseline clinical and imaging data required for risk assessment using the pre-specified machine learning model.
- Ability to provide written informed consent, or inclusion under ethics committee-approved procedures.
Who cannot join
- Confirmed extrahepatic metastasis at enrollment (baseline).
- History of other active malignancy within the past 5 years, except adequately treated non-melanoma skin cancer or in situ carcinoma.
- Incomplete baseline clinical information that precludes model-based risk assessment.
- Expected survival < 3 months due to severe comorbidities.
- Participation in an interventional clinical trial that may substantially alter follow-up strategy or metastasis assessment.
Trial locations and contacts
1 site in 1 country.
China1 site
Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
Wuhan, Hubei, 430030
About this study
This is a multicenter prospective observational cohort study in adults with hepatocellular carcinoma (HCC) without baseline extrahepatic metastasis who are receiving routine clinical management and follow-up at participating centers. The study evaluates the real-world implementation and clinical utility of a locked machine learning-guided risk stratification strategy for predicting lung and bone metastasis and supporting risk-stratified surveillance. The locked strategy uses prespecified 12-month risk thresholds and linked care pathways and is implemented without retraining or threshold revision. No study-mandated treatment or surveillance assignment is performed; clinical care remains at physician discretion according to local practice. The study assesses model transportability and calibration, implementation outcomes (including completion of prespecified actions, timeliness of action, and treatment activation), clinically actionable detection outcomes, patient-important outcomes, and longer-term survival. Comparative analyses use centre- and calendar-epoch-aligned usual-care episodes as the primary observational comparator.
Read the detailed description
Background and Rationale: Hepatocellular carcinoma (HCC) carries a substantial risk of postoperative or post-treatment recurrence and extrahepatic metastasis, which may affect prognosis and management opportunities. Early identification of patients at increased risk of extrahepatic metastasis may support more appropriate surveillance intensity, earlier multidisciplinary review, and more timely treatment planning.
Study Objectives: This study prospectively evaluates the real-world transportability, calibration, implementation characteristics, and clinical utility of a previously developed and locked machine learning-guided risk stratification strategy for extrahepatic metastasis in HCC, with a focus on lung and bone metastasis.
Study Design: This is a multicenter prospective observational cohort study conducted in routine clinical practice. Participants are enrolled and followed without randomization or study-mandated treatment allocation. The locked strategy includes endpoint-specific lung and bone metastasis risk modules, fixed 12-month risk thresholds, and linked risk-stratified surveillance recommendations. The prospective program includes staged real-world implementation, including an independent new-centre replication phase using the unchanged locked package.
Study Population: Adults with HCC without baseline extrahepatic metastasis at the first eligible risk assessment who are receiving routine care at participating centers.
Study Procedures and Data Collection: Baseline demographics, liver disease etiology, tumor burden and stage, liver reserve and performance status, biomarkers, imaging, treatment intent, follow-up imaging, occurrence and timing of extrahepatic metastasis, downstream management, implementation metrics, and clinical outcomes are collected prospectively from routine care records and study documentation.
Outcomes and Analytic Framework: The study evaluates incident extrahepatic metastasis, overall survival, and prespecified implementation and clinical utility outcomes, including completion of prespecified action, time to action, treatment activation, clinically actionable detection, symptom-driven detection, acute deterioration, and resource-related outcomes where available. Comparative implementation analyses use aligned usual-care episodes from the same centers and prespecified calendar epochs as the primary observational comparator. Any strategy-emulation or comparative-effectiveness analyses will be reported as observational estimates and will not be interpreted as randomized treatment effects.
Registry and timing statement (transparency \& status): This study was registered on ClinicalTrials.gov (NCT07444905) in February 2026, after study initiation. At the time of registration participant enrollment had ended and long-term follow-up for secondary endpoints remained ongoing. Primary outcome data collection is anticipated to be completed by 2026-12-30 and full study completion is anticipated by 2026-12-31. Overall Recruitment Status on the registry is recorded as Active, not recruiting. The timing of registration reflects administrative and multi-centre onboarding/IT coordination delays.
Background and rationale: Hepatocellular carcinoma (HCC) carries a substantial risk of postoperative or post-treatment recurrence and extrahepatic metastasis, which may affect prognosis and management opportunities. Early identification of patients at increased risk of extrahepatic metastasis may support more appropriate surveillance intensity, earlier multidisciplinary review, and more timely treatment planning.
Study objectives and design: This multicentre prospective observational cohort study evaluates the real-world transportability, calibration, implementation characteristics, and clinical utility of a previously developed and locked machine-learning guided risk-stratification strategy for extrahepatic metastasis in HCC (lung and bone modules). Participants are enrolled and followed in routine care without randomization or study-mandated treatment allocation. The locked strategy comprises endpoint-specific risk modules, fixed 12-month risk thresholds, and linked risk-stratified surveillance recommendations. The prospective programme includes staged real-world implementation and a prespecified independent new-centre replication phase that reused the unchanged locked package.
Governance and freeze evidence: Crucially, key governance objects (protocol v1.0, prespecified thresholds, SOP, statistical analysis plan, and code release tagged v1.0) were archived and time-stamped prior to the first live implementation. To enable independent verification, the following archived objects and logs are provided in the Supplementary Materials: NCT07444905_Study_Protocol;NCT07444905_Model_Lock_and_Version_Governance_Note;NCT07444905_Statistical_Analysis_Plan;NCT07444905_Endpoint_Definitions_and_Adjudication_Charter.
Wave-2 replication and auditability: Wave 2 was a prespecified independent new-centre prospective replication performed in different health systems and with different governance and deployment teams; it reused the unchanged locked package (v1.0) without retraining, recalibration, threshold revision, or SOP remapping. Supplementary materials include activation logs and time-stamped governance evidence documenting unchanged package use, and an independent recomputation/audit summary demonstrating that the analysis plan and codebase were fixed prior to implementation.
Outcomes and analytic framework: The study prospectively collects baseline demographics, liver disease etiology, tumor burden and stage, liver reserve and performance status, biomarkers, imaging, treatment intent, follow-up imaging, occurrence and timing of extrahepatic metastasis, downstream management, implementation metrics, and clinical outcomes. Primary and secondary outcomes, implementation metrics, and the prespecified analytic approach are described in the protocol and SAP (see Supplementary Materials).
- Conditions
- HCC - Hepatocellular Carcinoma, Machine Learning, Evaluation
- Being tested
- Machine Learning-Based Risk Assessment
- Medical subject headings
- Carcinoma, Hepatocellular
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Machine Learning-Based Risk AssessmentOther
Point-of-care use of a locked machine learning-guided risk assessment tool with fixed thresholds and linked risk-stratified surveillance recommendations; no study-mandated treatment assignment is performed
| Study group | Role | What they receive |
|---|---|---|
| Prospective Observational Cohort | Adults with hepatocellular carcinoma without baseline extrahepatic metastasis enrolled in a prospective observational cohort to evaluate a locked machine learning-guided risk stratification strategy for predicting lung and bone metastasis and supporting risk-stratified surveillance in routine practice. No experimental interventions are assigned, and clinical management remains at physician discretion. Receives: Other: Machine Learning-Based Risk Assessment |
What is being measured
The primary outcome is the main question the study is designed to answer.
Completion of a Prespecified Pathway-Concordant Action Within 60 Days
Proportion of eligible index episodes with completion of at least one prespecified pathway-concordant action within 60 days after the eligible index assessment. A pathway-concordant action was defined as SOP-concordant multidisciplinary team review, escalated lung- or bone-metastasis-directed imaging, or referral.
Measured: Day 0 to day 60 after the eligible index assessment.
Secondary outcomes (2)
Overall survival (OS)
Time from baseline (enrollment) to death from any cause; censored at last known alive date.
Measured: Up to 36 months
Completion of a Prespecified Action Within 60 Days
Completion of the prespecified risk-stratified surveillance or management action within 60 days after the first eligible locked risk assessment.
Measured: Completion of the prespecified risk-stratified surveillance or management action within 60 days after the first eligible locked risk assessment.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Mar 2026
- Study start1 Feb 2022
- Primary completion30 Dec 2026 (estimated)
- Study completion31 Dec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for HCC - Hepatocellular CarcinomaStudies of the same condition, open and under way.
- More trials run by Tongji HospitalThe 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
- Prospective
- Enrolment
- 1,523 participants (actual)
- Target duration
- 36 Months
Sponsor and investigators
- Lead sponsor
- Tongji Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Chen Xiaoping, Tongji Hospital
- Investigators
- Zhao Huang, Study director, Tongji Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07444905
- Sponsor's protocol ID
- MLEHM-010
- Status last verified
- May 2026
- First submitted
- 24 Feb 2026
- Last updated
- 3 Jun 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 3 Jun 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prospective Evaluation of a Locked Risk-Stratified Surveillance Strategy for Extrahepatic Metastasis in Hepatocellular Carcinoma
- ClinicalTrials.gov ID
- NCT07444905
- Acronym / sponsor ID
- MLEHM-010
- Conditions
- HCC - Hepatocellular Carcinoma, Machine Learning, Evaluation
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 1,523 participants (actual)
- Lead sponsor
- Tongji HospitalUniversity, hospital or other
- Study start
- 1 Feb 2022 (actual)
- Primary completion
- 30 Dec 2026 (estimated)
- Study completion
- 31 Dec 2026 (estimated)
- First posted
- 3 Mar 2026 (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.
This is a multicenter prospective observational cohort study in adults with hepatocellular carcinoma (HCC) without baseline extrahepatic metastasis who are receiving routine clinical management and follow-up at participating centers. The study evaluates the real-world implementation and clinical utility of a locked machine learning-guided risk stratification strategy for predicting lung and bone metastasis and supporting risk-stratified surveillance. The locked strategy uses prespecified 12-month risk thresholds and linked care pathways and is implemented without retraining or threshold revision. No study-mandated treatment or surveillance assignment is performed; clinical care remains at physician discretion according to local practice. The study assesses model transportability and calibration, implementation outcomes (including completion of prespecified actions, timeliness of action, and treatment activation), clinically actionable detection outcomes, patient-important outcomes, and longer-term survival. Comparative analyses use centre- and calendar-epoch-aligned usual-care episodes as the primary observational comparator.
Detailed description
Background and Rationale: Hepatocellular carcinoma (HCC) carries a substantial risk of postoperative or post-treatment recurrence and extrahepatic metastasis, which may affect prognosis and management opportunities. Early identification of patients at increased risk of extrahepatic metastasis may support more appropriate surveillance intensity, earlier multidisciplinary review, and more timely treatment planning.
Study Objectives: This study prospectively evaluates the real-world transportability, calibration, implementation characteristics, and clinical utility of a previously developed and locked machine learning-guided risk stratification strategy for extrahepatic metastasis in HCC, with a focus on lung and bone metastasis.
Study Design: This is a multicenter prospective observational cohort study conducted in routine clinical practice. Participants are enrolled and followed without randomization or study-mandated treatment allocation. The locked strategy includes endpoint-specific lung and bone metastasis risk modules, fixed 12-month risk thresholds, and linked risk-stratified surveillance recommendations. The prospective program includes staged real-world implementation, including an independent new-centre replication phase using the unchanged locked package.
Study Population: Adults with HCC without baseline extrahepatic metastasis at the first eligible risk assessment who are receiving routine care at participating centers.
Study Procedures and Data Collection: Baseline demographics, liver disease etiology, tumor burden and stage, liver reserve and performance status, biomarkers, imaging, treatment intent, follow-up imaging, occurrence and timing of extrahepatic metastasis, downstream management, implementation metrics, and clinical outcomes are collected prospectively from routine care records and study documentation.
Outcomes and Analytic Framework: The study evaluates incident extrahepatic metastasis, overall survival, and prespecified implementation and clinical utility outcomes, including completion of prespecified action, time to action, treatment activation, clinically actionable detection, symptom-driven detection, acute deterioration, and resource-related outcomes where available. Comparative implementation analyses use aligned usual-care episodes from the same centers and prespecified calendar epochs as the primary observational comparator. Any strategy-emulation or comparative-effectiveness analyses will be reported as observational estimates and will not be interpreted as randomized treatment effects.
Registry and timing statement (transparency \& status): This study was registered on ClinicalTrials.gov (NCT07444905) in February 2026, after study initiation. At the time of registration participant enrollment had ended and long-term follow-up for secondary endpoints remained ongoing. Primary outcome data collection is anticipated to be completed by 2026-12-30 and full study completion is anticipated by 2026-12-31. Overall Recruitment Status on the registry is recorded as Active, not recruiting. The timing of registration reflects administrative and multi-centre onboarding/IT coordination delays.
Background and rationale: Hepatocellular carcinoma (HCC) carries a substantial risk of postoperative or post-treatment recurrence and extrahepatic metastasis, which may affect prognosis and management opportunities. Early identification of patients at increased risk of extrahepatic metastasis may support more appropriate surveillance intensity, earlier multidisciplinary review, and more timely treatment planning.
Study objectives and design: This multicentre prospective observational cohort study evaluates the real-world transportability, calibration, implementation characteristics, and clinical utility of a previously developed and locked machine-learning guided risk-stratification strategy for extrahepatic metastasis in HCC (lung and bone modules). Participants are enrolled and followed in routine care without randomization or study-mandated treatment allocation. The locked strategy comprises endpoint-specific risk modules, fixed 12-month risk thresholds, and linked risk-stratified surveillance recommendations. The prospective programme includes staged real-world implementation and a prespecified independent new-centre replication phase that reused the unchanged locked package.
Governance and freeze evidence: Crucially, key governance objects (protocol v1.0, prespecified thresholds, SOP, statistical analysis plan, and code release tagged v1.0) were archived and time-stamped prior to the first live implementation. To enable independent verification, the following archived objects and logs are provided in the Supplementary Materials: NCT07444905_Study_Protocol;NCT07444905_Model_Lock_and_Version_Governance_Note;NCT07444905_Statistical_Analysis_Plan;NCT07444905_Endpoint_Definitions_and_Adjudication_Charter.
Wave-2 replication and auditability: Wave 2 was a prespecified independent new-centre prospective replication performed in different health systems and with different governance and deployment teams; it reused the unchanged locked package (v1.0) without retraining, recalibration, threshold revision, or SOP remapping. Supplementary materials include activation logs and time-stamped governance evidence documenting unchanged package use, and an independent recomputation/audit summary demonstrating that the analysis plan and codebase were fixed prior to implementation.
Outcomes and analytic framework: The study prospectively collects baseline demographics, liver disease etiology, tumor burden and stage, liver reserve and performance status, biomarkers, imaging, treatment intent, follow-up imaging, occurrence and timing of extrahepatic metastasis, downstream management, implementation metrics, and clinical outcomes. Primary and secondary outcomes, implementation metrics, and the prespecified analytic approach are described in the protocol and SAP (see Supplementary Materials).
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 36 Months
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Prospective Observational Cohort | – | Other: Machine Learning-Based Risk AssessmentAdults with hepatocellular carcinoma without baseline extrahepatic metastasis enrolled in a prospective observational cohort to evaluate a locked machine learning-guided risk stratification strategy for predicting lung and bone metastasis and supporting risk-stratified surveillance in routine practice. No experimental interventions are assigned, and clinical management remains at physician discretion. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Adult patients with hepatocellular carcinoma (HCC) without evidence of extrahepatic metastasis at baseline who are receiving standard-of-care management and undergoing prospective follow-up in routine clinical practice. Participants are enrolled in a prospective observational cohort to evaluate a machine learning-based risk assessment strategy for predicting extrahepatic metastasis and supporting risk-adapted surveillance.
Key inclusion criteria (6 listed)
- Age ≥ 18 years.
- Diagnosis of hepatocellular carcinoma (HCC) confirmed by histopathology or accepted radiologic criteria per international guidelines.
- No evidence of extrahepatic metastasis at baseline evaluation.
- Receiving standard-of-care management with planned longitudinal follow-up in routine clinical practice.
- Availability of baseline clinical and imaging data required for risk assessment using the pre-specified machine learning model.
Key exclusion criteria (5 listed)
- Confirmed extrahepatic metastasis at enrollment (baseline).
- History of other active malignancy within the past 5 years, except adequately treated non-melanoma skin cancer or in situ carcinoma.
- Incomplete baseline clinical information that precludes model-based risk assessment.
- Expected survival < 3 months due to severe comorbidities.
- Participation in an interventional clinical trial that may substantially alter follow-up strategy or metastasis assessment.
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 |
|---|---|---|
| Machine Learning-Based Risk AssessmentPoint-of-care use of a locked machine learning-guided risk assessment tool with fixed thresholds and linked risk-stratified surveillance recommendations; no study-mandated treatment assignment is performed | Other | Prospective Observational Cohort |
Primary outcome
Completion of a Prespecified Pathway-Concordant Action Within 60 Days
Time frame: Day 0 to day 60 after the eligible index assessment.
Proportion of eligible index episodes with completion of at least one prespecified pathway-concordant action within 60 days after the eligible index assessment. A pathway-concordant action was defined as SOP-concordant multidisciplinary team review, escalated lung- or bone-metastasis-directed imaging, or referral.
2 secondary outcomes
Overall survival (OS)
Time frame: Up to 36 months
Completion of a Prespecified Action Within 60 Days
Time frame: Completion of the prespecified risk-stratified surveillance or management action within 60 days after the first eligible locked risk assessment.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 3 Jun 2026.
- Individual participant dataSharing planned: Undecided
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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.
Zhao Huang study director
Tongji 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 HCC - Hepatocellular Carcinoma and Machine Learning, run by Tongji Hospital at 1 site in China.
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 6 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: under way, not looking for participants, as of the sponsor's last update on 3 Jun 2026. 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 China. 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?
This study is still under way. Results are not available in the source record yet.
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?
Completion of a Prespecified Pathway-Concordant Action Within 60 Days (time frame: Day 0 to day 60 after the eligible index assessment.). 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 3 Jun 2026.