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| Name | Class |
|---|---|
| Eastern Hepatobiliary Surgery Hospital | OTHER |
| The First Affiliated Hospital of Zhengzhou University | OTHER |
| Jiangsu Cancer Institute & Hospital | OTHER |
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This study focused on exploring new comprehensive treatment strategies for patients with unresectable combined hepatocellular-cholangiocarcinoma, classifying patients with CHC subtypes based on the combination of artificial intelligence and multi-omics, and exploring the optimal treatment strategies for patients with different subtypes, helping clinicians to screen the most beneficial groups of various treatment schemes, and providing new ideas for safe treatment of high-risk patients.
This will be a multicenter observational study that will be conducted at several leading liver cancer treatment centers. The study will include adult patients with histologically/cytologically confirmed unresectable CHC. Collect patient genomics, proteomics, immune microenvironment, pathology reports, medical images and clinical electronic medical records, etc., to form high-quality and deeply labeled data sets to support the subsequent development and application of AI large models. Based on multi-source heterogeneous data of CHC patients, a large model for comprehensive diagnosis and treatment was constructed. Firstly, multi-modal data of different stages of disease were integrated by using cross-modal multi-course fusion technology to achieve efficient fusion of complex data. Secondly, by fine-tuning the large model, tasks such as CHC classification, prognosis inference and treatment plan recommendation are accurately completed, and potential information in the diagnosis and treatment process is mined.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Interventional therapies combined with or without systemic drugs | Combination Product | The study will include adult patients with histologically/cytologically confirmed unresectable CHC. Collect patient genomics, proteomics, immune microenvironment, pathology reports, medical images and clinical electronic medical records, etc., to form high-quality and deeply labeled data sets to support the subsequent development and application of AI large models. Based on multi-source heterogeneous data of CHC patients, a large model for comprehensive diagnosis and treatment was constructed. Firstly, multi-modal data of different stages of disease were integrated by using cross-modal multi-course fusion technology to achieve efficient fusion of complex data. Secondly, by fine-tuning the large model, tasks such as CHC classification, prognosis inference and treatment plan recommendation are accurately completed, and potential information in the diagnosis and treatment process is mined. |
| Measure | Description | Time Frame |
|---|---|---|
| Overall Survival(OS) | The OS is defined as the time from the initiation of any combination treatment to death due to any cause. | up to approximately 2 years |
| Measure | Description | Time Frame |
|---|---|---|
| Progression free survival(PFS) per Response Evaluation Criteria in Solid Tumors Version 1.1 (RECIST 1.1) | 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 death due to any cause, whichever occurs first. | up to approximately 2 years |
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Inclusion Criteria:
Exclusion Criteria:
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The target population for the planned retrospective analysis of this project is patients with pathologically confirmed mixed hepatocellular cholangiocarcinoma, based on the 2024 NCCN Clinical Practice Guidelines in Oncology: Hepatocellular Carcinoma [Version 2.2024]) and China's Primary Liver Cancer Diagnosis and Treatment Guidelines (2024) are defined as unresectable patients.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Gao-Jun Teng, M.D | Contact | +86-02583272121 | gjteng@vip.sina.com |
| Name | Affiliation | Role |
|---|---|---|
| Gao-Jun Teng, M.D | Zhongda hospital, Southeast university, Nanjing, China | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Zhongda Hospital | Recruiting | Nanjing | Jiangsu | China |
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| Yunnan Cancer Hospital |
| OTHER |
| Zhejiang Cancer Hospital | OTHER |
| Shanghai Zhongshan Hospital | OTHER |
| Sun Yat-Sen University Cancer Center | OTHER |
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| PFS per Modified Response Evaluation Criteria in Solid Tumors (mRECIST) |
The PFS is defined as the time from the initiation of any combination treatment to the first documented progressive disease (according to mRECIST) or death due to any cause, whichever occurs first. |
| up to approximately 2 years |
| Objective response rate(ORR) per RESCIST 1.1 | The ORR is defined as the proportion of patients with a documented complete response(CR) or partial response(PR) per RECIST 1.1. | up to approximately 2 years |
| ORR per mRECIST | The ORR is defined as the proportion of patients with a documented CR or PR per mRECIST. | up to approximately 2 years |
| Duration of Response (DOR) per RESCIST 1.1 | DOR is determined by disease assessment and is defined as the time from the first documented evidence of a response of CR or PR until the first documented disease progression (according to RESCIST 1.1) or death due to any cause, whichever occurs first. | up to approximately 2 years |
| DOR per mRECIST | DOR is determined by disease assessment and is defined as the time from the first documented evidence of a response of CR or PR until the first documented disease progression (according to mRECIST) or death due to any cause, whichever occurs first. | up to approximately 2 years |
| Disease Control Rate (DCR) per RESCIST 1.1 | DCR is defined as the percentage of participants who have a best overall response of CR, PR, or stable disease (SD)per RESCIST 1.1. | up to approximately 2 years |
| DCR per mRECIST | DCR is defined as the percentage of participants who have a best overall response of CR, PR, or stable disease (SD) per mRECIST. | up to approximately 2 years |
| Adverse event(AE) per Common Terminology Criteria for Adverse Events(CTCAE) 5.0 | The percentage and degree of patients who experience at least one AE, whether or not considered related to the treatment, according to CTCAE version 5.0. | up to approximately 2 years |
| ID | Term |
|---|---|
| D008113 | Liver Neoplasms |
| ID | Term |
|---|---|
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D004066 | Digestive System Diseases |
| D008107 | Liver Diseases |
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