Study on the Classification of Comprehensive Treatment Effect of Hepatocellular Carcinoma
NCT Number: NCT06542796
Status: NOT_YET_RECRUITING
Study Type: INTERVENTIONAL
Phases: NA
Conditions: Hepatocellular Carcinoma|Immunotherapy
Interventions: PROCEDURE: Immunotherapy combined with targeted therapy|OTHER: Standard treatment plan
Sponsor: Second Affiliated Hospital, School of Medicine, Zhejiang University
Sex: ALL
Age: ADULT, OLDER_ADULT
Enrollment: 100
Study Design: Allocation: RANDOMIZED|Intervention Model: SINGLE_GROUP|Masking: TRIPLE (PARTICIPANT, CARE_PROVIDER, OUTCOMES_ASSESSOR)|Primary Purpose: SCREENING
Start Date: 2024-09-01
Completion Date: 2027-05-01

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.

Primary Outcome Measures: Evaluation of the efficacy of patient treatment, 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, 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