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.
This study will integrate a retrospective cohort with a prospective observational cohort. Multimodal data will be collected in the prospective cohort to validate the AI-based imaging model developed from the retrospective cohort. In addition, advanced multi-omics technologies will be incorporated to characterize tumor heterogeneity and the immune microenvironment, thereby supporting early and precise guidance for TACE combined with immunotherapy and targeted therapy in HCC.
Study Type
OBSERVATIONAL
Enrollment
1,170
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
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.
Time frame: From enrollment to approximately 2 years
Objective response rate(ORR)
The ORR is defined as the proportion of patients with a documented complete response(CR) or partial response(PR) per RECIST 1.1 or per mRECIST.
Time frame: up to approximately 2 years
Overall Survival(OS)
The OS is defined as the time from the initiation of any combination treatment to death due to any cause.
Time frame: up to approximately 2 years
Progression free survival(PFS)
The PFS is defined as the time from the initiation of any combination treatment to the first documented progressive disease (according to RECIST 1.1 or mRECIST) or death due to any cause, whichever occurs first.
Time frame: up to approximately 2 years
Other prediction performance of the model
Evaluation of the accuracy, sensitivity, and specificity of the prediction model in clinical application
Time frame: From enrollment to approximately 2 years
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