Study on the Classification of Comprehensive Treatment Effect of Hepatocellular Carcinoma
- Conditions
- ImmunotherapyHepatocellular Carcinoma
- Interventions
- Procedure: Immunotherapy combined with targeted therapyOther: Standard treatment plan
- Registration Number
- NCT06542796
- Lead Sponsor
- Second Affiliated Hospital, School of Medicine, Zhejiang University
- Brief Summary
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.
- 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.
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 100
- Patients with advanced hepatocellular carcinoma
- 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 & Design
- Study Type
- INTERVENTIONAL
- Study Design
- PARALLEL
- Arm && Interventions
Group Intervention Description Comprehensive treatment group Immunotherapy combined with targeted therapy Immunotherapy combined with targeted therapy non-comprehensive treatment group Standard treatment plan Standard treatment plan
- Primary Outcome Measures
Name Time Method Evaluation of the efficacy of patient treatment 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.
The predictive accuracy of the constructed model 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.
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
2ndAffiliated Hospital, School of Medicine, Zhejiang University
🇨🇳Hangzhou, Zhejiang, China