Study on the Classification of Comprehensive Treatment Effect of Hepatocellular Carcinoma

Condition(s) studied

Investigational drug(s) / intervention(s)

Immunotherapy combined with targeted therapy: Immunotherapy combined with targeted therapy

Standard treatment plan: Standard treatment plan

Study 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.

Eligibility

Primary outcome measure(s)

• 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.

Trial sites (1)

More Second Affiliated Hospital, Zhejiang University, School of Medicine trials in China

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