A Generative Model-based System for Predicting Survival and Guiding Treatment Decisions in Patients With Unresectable Hepatocellularcarcinoma Undergoing Transcatheter Arterial Chemoembolization in Combination With Immunotherapy and Targeted Therapy

July 10, 2025 updated by: Gao-jun Teng, Zhongda Hospital

A Generative Model-based System for Predicting Survival and Guiding Treatment Decisions in Patients With Unresectable Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization in Combination With Immunotherapy and Targeted Therapy

The entry point of this study is the proposition of "generative longitudinal prediction," which utilizes only pre-treatment imaging to create high-fidelity predictions of post-treatment imaging. This approach effectively overcomes the clinical challenge of acquiring genuine longitudinal follow-up data. This paradigm shift not only tackles the scarcity of longitudinal data but also introduces an innovative method for treatment simulation using digital twins. Clinicians can intuitively assess the potential efficacy of various treatment plans before intervention through virtually generated multi-timepoint imaging, providing a visual foundation for personalized treatment decisions. This research merges generative AI with dynamic risk models to achieve: 1) a transition from static assessment to dynamic simulation; 2) earlier survival predictions; and 3) personalized optimization of treatment plans. By eliminating dependence on longitudinal data, we aim to deliver more precise and individualized treatment decision support for advanced liver cancer patients, ultimately enhancing survival outcomes and quality of life.

Study Overview

Status

Active, not recruiting

Conditions

Intervention / Treatment

Detailed Description

The entry point of this study is the proposition of "generative longitudinal prediction," which utilizes only pre-treatment imaging to create high-fidelity predictions of post-treatment imaging. This approach effectively overcomes the clinical challenge of acquiring genuine longitudinal follow-up data. This paradigm shift not only tackles the scarcity of longitudinal data but also introduces an innovative method for treatment simulation using digital twins. Clinicians can intuitively assess the potential efficacy of various treatment plans before intervention through virtually generated multi-timepoint imaging, providing a visual foundation for personalized treatment decisions. This research merges generative AI with dynamic risk models to achieve: 1) a transition from static assessment to dynamic simulation; 2) earlier survival predictions; and 3) personalized optimization of treatment plans. By eliminating dependence on longitudinal data, we aim to deliver more precise and individualized treatment decision support for advanced liver cancer patients, ultimately enhancing survival outcomes and quality of life. The model was developed in a retrospective cohort, with validation and testing conducted in multiple retrospective and prospective cohorts, respectively.

Study Type

Observational

Enrollment (Estimated)

550

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • China
    • Jiangsu
      • Changzhou, Jiangsu, China, 213003
        • Zhongda hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Unresectable hepatocellular carcinoma undergoing TACE in combination with immunotherapy plus targeted therapy

Description

Inclusion Criteria:

  • Diagnosed as unresectable hepatocellular carcinoma (HCC) by histopathology and/or clinical diagnosis (typical imaging features, clinical manifestations, laboratory tests, etc.) (Reference: Guidelines for Diagnosis and Treatment of Primary Liver Cancer (2024 Edition));
  • Patients with unresectable HCC receiving TACE combined with targeted immunotherapy;
  • Liver function classified as Child-Pugh A or B;
  • Aged 18 or above, regardless of gender;
  • Expected survival time ≥3 months;
  • ECOG PS score ≤2;
  • Meeting the following laboratory parameters: a) Hematologic function: Absolute neutrophil count ≥1.0×10⁹/L; Platelet count ≥50×10⁹/L; Hemoglobin ≥90 g/L; International normalized ratio (INR) <1.7 or prothrombin time prolongation ≤4 seconds; b) Liver function: ALT/AST ≤5× upper limit of normal (ULN); Total bilirubin ≤210 μmol/L [≤2.38 mg/dL]; Albumin ≥28 g/L; c) Renal function: Serum creatinine ≤1.5× ULN.

Exclusion Criteria:

  • Concurrent presence of other malignant tumors besides HCC;
  • Moderate to severe ascites (ascites scoring 3 points on the Child-Pugh scale); - - Receipt of other first-line, second-line, or third-line systemic therapies (including any regimen of systemic treatment) or any local therapies (including transcatheter interventional therapy, ablation therapy, internal/external radiotherapy, etc.), as well as surgical resection or herbal medicine within 4 weeks prior to TACE combined with targeted immunotherapy;
  • Incomplete data, such as missing baseline laboratory test results, unavailable or poor-quality imaging data, or lack of prognostic information;
  • Severe liver dysfunction: e.g., decompensated cirrhosis or other liver diseases significantly affecting bilirubin levels;
  • Severe comorbidities: e.g., refractory hypertension (blood pressure remaining above 150/100 mm Hg despite optimal medication), persistent arrhythmia (CTCAE grade 2 or higher), atrial fibrillation of any degree, prolonged QTc interval (>450 ms in males or >470 ms in females), renal insufficiency, etc.;
  • Co-infection with human immunodeficiency virus (HIV) or acquired immunodeficiency syndrome (AIDS);
  • Pregnant or breastfeeding women;
  • Acute or chronic psychiatric disorders (including those affecting participant enrollment, treatment intervention, or follow-up).

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
development cohort, validation cohort, test cohort
Other: Generative model
Prospectively enroll pretreatment imaging data from patients with unresectable hepatocellular carcinoma undergoing TACE in combination with immunotherapy plus targeted therapy. Utilize a generative model to create virtual images that represent optimal treatment responses, and compare these virtual images with actual treatment response images collected during follow-up to evaluate the reliability of the generative model.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Overall survival
Time Frame: Through study completion, an average of 20 months
defined as the time from the initial of combined therapy to death from any cause
Through study completion, an average of 20 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Zhongda Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 1, 2024

Primary Completion (Estimated)

January 1, 2026

Study Completion (Estimated)

February 1, 2026

Study Registration Dates

First Submitted

July 1, 2025

First Submitted That Met QC Criteria

July 10, 2025

First Posted (Actual)

July 15, 2025

Study Record Updates

Last Update Posted (Actual)

July 15, 2025

Last Update Submitted That Met QC Criteria

July 10, 2025

Last Verified

July 1, 2025

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • GenTI-uHCC

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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