Study on the Classification of Comprehensive Treatment Effect of Hepatocellular Carcinoma

February 5, 2025 updated by: Second Affiliated Hospital, School of Medicine, Zhejiang University
Through a retrospective study of patients who underwent comprehensive treatment for hepatocellular carcinoma at the Second Affiliated Hospital of Zhejiang University, we explored the risk factors related to the sensitivity of comprehensive treatment. We used the PD-L1 expression level of patients before comprehensive treatment，characteristic morphology of tertiary lymphoid structures, as well as other parameters, are used to construct a liver cancer comprehensive treatment efficacy evaluation model. Using this liver cancer comprehensive treatment efficacy evaluation model, we conducted a randomized controlled trial on whether to receive comprehensive treatment for liver cancer patients to verify the accuracy and practical value of the model.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed Description

As of 2020, hepatocellular carcinoma (HCC) is the sixth leading cause of cancer-related deaths, making it one of the world's major public health issues. The incidence of HCC is increasing year by year, from 14 million cases worldwide in 2012 to an estimated 22 million cases by 2030. Most HCC patients are not diagnosed until late stages, thus missing the optimal treatment window. In recent years, comprehensive therapy with immune targeting as the core has made breakthrough progress in the treatment of advanced liver cancer, bringing good news to patients with advanced liver cancer. Clinical trials have shown that immunotherapy combined with targeted therapy is effective in the treatment of unresectable hepatocellular carcinoma. Patients have significant clinical value. However, the therapeutic effect of immune targeting varies depending on the complex tumor microenvironment of HCC. Therefore, there is an urgent need to establish an efficacy evaluation model for comprehensive treatment to accurately classify and stratify patients and select the best treatment plan.

Intratumoral T cell and B cell infiltration has been extensively studied and is associated with good prognosis in most tumors. In recent years, tertiary lymphoid structures (TLS) have gradually gained in-depth understanding. Tertiary lymphoid structures are lymphatic aggregates formed at sites of inflammation in autoimmune diseases, infections, and cancers. They can provide local antigen presentation sites and generate effector T cells and central memory T cells, thereby providing humoral and cellular anti-tumor specificity. Sexual immune response provides an important microenvironment. Further studies have shown that the presence of intratumoral TLS is associated with reduced risk of recurrence and improved survival in most solid tumors, and mature TLS was found to be a key site of tumor-specific immune responses in pancreatic ductal adenocarcinoma, which is consistent with immunotherapy. related to efficacy. In addition, more and more studies have found that clinical characteristics such as vascular endothelial growth factor (VEGF) levels are related to the effect of comprehensive treatment of liver cancer. Studies have shown that plasma VEGF levels are significantly related to the survival rate of patients with hepatocellular carcinoma, and VEGF levels are important for their prognosis. Stratification has excellent clinical value.

Therefore, this study focused on the characteristic parameters of liver cancer tumor microenvironment such as TLS, PD-L1 expression level, and VEGF level to construct a liver cancer comprehensive treatment efficacy evaluation model to guide the selection of treatment options.

The predictive accuracy of the constructed model was determined by measuring the specificity, sensitivity, and area under the receiver operating characteristic (ROC) curve in the validation sample. Discrimination refers to the ability of a predictive model to accurately identify patients at low and high risk for the event under investigation, usually expressed as the area under the ROC curve. A predictive model with an ROC of 0.75 is considered to have good discrimination, whereas an area of 0.5 is considered equivalent to a coin toss.

Study Type

Interventional

Enrollment (Estimated)

100

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • China
    • Zhejiang
      • Hangzhou, Zhejiang, China, 310009
        • Recruiting
        • 2ndAffiliated Hospital, School of Medicine, Zhejiang University
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • Patients with advanced hepatocellular carcinoma

Exclusion Criteria:

  • Have comorbidities of severe diabetes, heart failure, liver and/or kidney failure
  • Have a history of schizophrenia
  • Have a history of other malignant tumors or metastatic liver tumors discovered after surgery
  • Received anti-tumor drugs for other diseases
  • Special groups such as pregnant and lactating women.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Treatment
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Comprehensive treatment group
Immunotherapy combined with targeted therapy
Procedure: Immunotherapy combined with targeted therapy
Immunotherapy combined with targeted therapy
Active Comparator: non-comprehensive treatment group
Standard treatment plan
Other: Standard treatment plan
Standard treatment plan

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Evaluation of the efficacy of patient treatment
Time Frame: Long-term follow-up of patients after treatment through the study completion, an average of 1 year
The treatment effects were assessed according to the Response Evaluation Criteria in Solid Tumors (RECIST) proposed by the American Cancer Institute. The treatment effects were divided into complete remission (CR), partial remission (PR), stable disease (SD), progressive disease (PD), objective response rate (ORR) = CR + PR, and disease control rate (DCR) = CR + PR + SD. All the data in this study were analyzed and processed with statistical software SPSS 24.0. The measurement data were expressed in mean ± SD (±s). When the measurement data conform to the normal distribution and the variance was homogeneous, a t-test was adopted. The counting data were described by N and %. The disordered classification data were compared by the χ2 test or Fisher's exact probability method. All tests were two-sided, and the difference was statistically significant when P < 0.05.
Long-term follow-up of patients after treatment through the study completion, an average of 1 year
The predictive accuracy of the constructed model
Time Frame: Long-term follow-up of patients after treatment through the study completion, an average of 1 year
The predictive accuracy of the constructed model was determined by measuring the specificity, sensitivity, and area under the receiver operating characteristic (ROC) curve in the validation sample. Discrimination refers to the ability of a predictive model to accurately identify patients at low and high risk for the event under investigation, usually expressed as the area under the ROC curve. A predictive model with an ROC of 0·75 is considered to have good discrimination, whereas an area of 0·5 is considered equivalent to a coin toss.All the data in this study were analyzed and processed with statistical software SPSS 24.0. All tests were two-sided, and the difference was statistically significant when P < 0.05.
Long-term follow-up of patients after treatment through the study completion, an average of 1 year

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Second Affiliated Hospital, School of Medicine, Zhejiang University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

September 1, 2024

Primary Completion (Estimated)

March 31, 2027

Study Completion (Estimated)

May 1, 2027

Study Registration Dates

First Submitted

June 4, 2024

First Submitted That Met QC Criteria

August 5, 2024

First Posted (Actual)

August 7, 2024

Study Record Updates

Last Update Posted (Actual)

March 25, 2025

Last Update Submitted That Met QC Criteria

February 5, 2025

Last Verified

March 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2024-0318

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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