Hepatocellular Carcinoma
Conditions
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.
Detailed description
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.
Interventions
OTHERArtificial Intelligence
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
Sponsors
Gao-jun Teng
Study design
Observational model
COHORT
Time perspective
OTHER
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
1. Retrospective Study Cohort 1.1 Inclusion Criteria Age ≥18 years; Patients with hepatocellular carcinoma confirmed by histopathology or clinical diagnosis; At least one intrahepatic lesion that is repeatedly measurable according to RECIST v1.1. 1.2
Exclusion criteria
Known sarcomatoid hepatocellular carcinoma or fibrolamellar hepatocellular carcinoma; Presence of other active malignancies within the past 5 years or concurrent active malignancies other than hepatocellular carcinoma; Missing preoperative imaging examinations, including CT or MRI, or poor image quality; Missing key baseline clinical data; Loss to follow-up after treatment. 2. Prospective Study Cohort 2.1 Inclusion Criteria Age ≥18 years; Patients with hepatocellular carcinoma confirmed by histopathology or clinical diagnosis; Scheduled to receive first-line TACE combined with immunotherapy and targeted therapy; At least one intrahepatic lesion that is repeatedly measurable according to RECIST v1.1; Expected survival of more than 3 months. 2.2
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Prediction Performance of the AI Model | From enrollment to approximately 2 years | 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. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Objective response rate(ORR) | up to approximately 2 years | 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. |
| Overall Survival(OS) | up to approximately 2 years | The OS is defined as the time from the initiation of any combination treatment to death due to any cause. |
| Progression free survival(PFS) | up to approximately 2 years | 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. |
| Other prediction performance of the model | From enrollment to approximately 2 years | Evaluation of the accuracy, sensitivity, and specificity of the prediction model in clinical application |
Contacts
CONTACTZhicheng Jin, MD
Outcome results
None listed