AI-Based Multimodal Integration for Tumor Microenvironment Analysis and Response Prediction in HCC Treated With TACE Plus Immunotherapy and Targeted Therapy (CHANCE2601)
Artificial Intelligence-Based Multimodal Data Integration for Tumor Microenvironment Analysis and Response Prediction in Hepatocellular Carcinoma Patients Undergoing TACE Combined With Immunotherapy and Targeted Therapy
1 other identifier
observational
1,170
0 countries
N/A
Brief Summary
This study aims to prospectively validate a retrospective cohort-derived AI-based multimodal model and explore tumor heterogeneity and the immune microenvironment to guide TACE combined with immunotherapy and targeted therapy in HCC.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started May 2026
Typical duration for all trials
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
May 7, 2026
CompletedFirst Posted
Study publicly available on registry
May 13, 2026
CompletedStudy Start
First participant enrolled
May 18, 2026
CompletedPrimary Completion
Last participant's last visit for primary outcome
May 31, 2027
ExpectedStudy Completion
Last participant's last visit for all outcomes
December 31, 2028
May 13, 2026
May 1, 2026
1 year
May 7, 2026
May 7, 2026
Conditions
Outcome Measures
Primary Outcomes (1)
Prediction Performance of the AI Model
The area under curve (AUC) of Receiver Operating Characteristic (ROC) curves o f the AI model in predicting the clinical outcomes in patients receiving TACE combined with immunotherapy and targeted therapy.
From enrollment to approximately 2 years
Secondary Outcomes (4)
Objective response rate(ORR)
up to approximately 2 years
Overall Survival(OS)
up to approximately 2 years
Progression free survival(PFS)
up to approximately 2 years
Other prediction performance of the model
From enrollment to approximately 2 years
Study Arms (2)
Retrospective cohort
Patients with hepatocellular carcinoma who received TACE combined with immunotherapy and targeted therapy, as well as other treatment modalities, will be retrospectively included. Multimodal data from this cohort will be used to develop and train the AI-based model.
Prospective cohort
Patients with hepatocellular carcinoma who receive TACE combined with immunotherapy and targeted therapy will be prospectively enrolled. Multimodal data, including clinical, imaging, and biospecimen-related data when available, will be collected to validate the AI-based multimodal model.
Interventions
Investigators utilize a AI-based supportive system to predict clinical outcomes for patients with hepatocellular carcinoma who received TACE combined with immunotherapy and targeted therapy
Eligibility Criteria
In the retrospective cohort, patients with HCC who received TACE combined with immunotherapy and targeted therapy, as well as other treatment modalities, will be retrospectively included. Multimodal data from this cohort will be used to develop and train the AI-based model. In the prospective cohort, patients with HCC who receive TACE combined with immunotherapy and targeted therapy will be prospectively enrolled. Multimodal data, including clinical, imaging, and biospecimen-related data when available, will be collected to validate the AI-based multimodal model.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Gao-jun Tenglead
Related Publications (3)
Zhong BY, Fan W, Guan JJ, Peng Z, Jia Z, Jin H, Jin ZC, Chen JJ, Zhu HD, Teng GJ. Combination locoregional and systemic therapies in hepatocellular carcinoma. Lancet Gastroenterol Hepatol. 2025 Apr;10(4):369-386. doi: 10.1016/S2468-1253(24)00247-4. Epub 2025 Feb 21.
PMID: 39993404BACKGROUNDJin ZC, Wei J, Xiao YD, Si A, Chen JJ, Zhu XL, Li JZ, Nie F, Ding R, Zhou HF, Ding W, Zhong BY, Xie Y, Hu HT, Yin GW, Ji JS, Zhang WH, Shi HB, Wu JB, Xu GH, Yuan CW, Yang WZ, Liu RB, Wu YM, Zheng CS, Xu AB, Huang MS, Li JP, Chen L, Wen SW, Wang YQ, Gu SZ, Li D, Wang D, Zhou GH, Wang WD, Peng Z, Wang X, Zhu HD, Tian J, Teng GJ. Decoding tumor heterogeneity with imaging biomarkers predicts response to TACE plus immunotherapy and targeted therapy in HCC (CHANCE2204). Hepatology. 2025 Nov 10. doi: 10.1097/HEP.0000000000001593. Online ahead of print.
PMID: 41213031BACKGROUNDVithayathil M, Koku D, Campani C, Nault JC, Sutter O, Ganne-Carrie N, Aboagye EO, Sharma R. Machine learning based radiomic models outperform clinical biomarkers in predicting outcomes after immunotherapy for hepatocellular carcinoma. J Hepatol. 2025 Oct;83(4):959-970. doi: 10.1016/j.jhep.2025.04.017. Epub 2025 Apr 17.
PMID: 40246150BACKGROUND
MeSH Terms
Conditions
Interventions
Condition Hierarchy (Ancestors)
Intervention Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- OTHER
- Target Duration
- 24 Months
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR INVESTIGATOR
- PI Title
- President
Study Record Dates
First Submitted
May 7, 2026
First Posted
May 13, 2026
Study Start
May 18, 2026
Primary Completion (Estimated)
May 31, 2027
Study Completion (Estimated)
December 31, 2028
Last Updated
May 13, 2026
Record last verified: 2026-05
Data Sharing
- IPD Sharing
- Will not share