Novel Subtypes and Treatment Strategies of Patients with Unresectable Combined Hepatocellular Cholangiocarcinoma Based on Multimodal Data

NCT ID: NCT06849180

Last Updated: 2025-02-27

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

198 participants

Study Classification

OBSERVATIONAL

Study Start Date

2024-12-31

Study Completion Date

2026-02-28

Brief Summary

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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.

Detailed Description

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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.

Conditions

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Combined Hepatocellular-cholangiocarcinoma Combined Hepatocellular Carcinoma and Cholangiocarcinoma Combined Hepatocellular and Cholangiocarcinoma

Study Design

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Observational Model Type

CASE_CONTROL

Study Time Perspective

CROSS_SECTIONAL

Interventions

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Interventional therapies combined with or without systemic drugs

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.

Intervention Type COMBINATION_PRODUCT

Eligibility Criteria

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Inclusion Criteria

1. age ≥18 years; diagnosis of CHC confirmed by histology or cytology;
2. patients with unresectable or metastatic CHC diagnosed on the basis of unresectable CHC who have received prior local therapy, systemic therapy, or a combination of both and have at least one measurable lesion (RECIST v1.1);
3. survival time ≥ 3 months;
4. ECOG PS 0-2;
5. Child-Pugh A/B.

Exclusion Criteria

1. pregnant women, lactating women, and men and women of childbearing age who are unwilling or unable to use effective contraception.
2. history of other malignant tumors within the past five years, unless these tumors have been completely treated and have been free of active disease for five years prior to the first dose and are at low risk of recurrence.
3. fully treated carcinoma in situ with no evidence of disease.
4. history of gastrointestinal bleeding or significant bleeding tendency (e.g., with known active ulcers, fecal occult blood, etc.) within the past six months that precludes inclusion in the study; gastroscopy is required if there is persistent fecal occult blood.
5. substantial organ transplantation or bone marrow transplantation within two years prior to the first dose, or active autoimmune disease requiring systemic therapy.
6. other conditions that the investigator deems unsuitable for inclusion in the study. Inadequate information, such as incomplete data from laboratory tests, missing or poor quality imaging data, no prognostic information, etc., that the investigator considers unsuitable for inclusion in the study.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Eastern Hepatobiliary Surgery Hospital

OTHER

Sponsor Role collaborator

The First Affiliated Hospital of Zhengzhou University

OTHER

Sponsor Role collaborator

Jiangsu Cancer Institute & Hospital

OTHER

Sponsor Role collaborator

Yunnan Cancer Hospital

OTHER

Sponsor Role collaborator

Zhejiang Cancer Hospital

OTHER

Sponsor Role collaborator

Shanghai Zhongshan Hospital

OTHER

Sponsor Role collaborator

Sun Yet-Sen University Cancer Center

OTHER

Sponsor Role collaborator

Zhongda Hospital

OTHER

Sponsor Role lead

Responsible Party

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Gao-jun Teng

Director of interventional and Vascular Surgery Department

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Gao-Jun Teng, M.D

Role: PRINCIPAL_INVESTIGATOR

Zhongda hospital, Southeast university, Nanjing, China

Locations

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Zhongda Hospital

Nanjing, Jiangsu, China

Site Status RECRUITING

Countries

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China

Central Contacts

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Gao-Jun Teng, M.D

Role: CONTACT

+86-02583272121

Facility Contacts

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Gao-Jun Teng, M.D

Role: primary

+86-02583272121

Other Identifiers

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2024040195

Identifier Type: -

Identifier Source: org_study_id

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