CT表现及血清指标预测免疫/靶向治疗对中晚期肝细胞癌的效果

目的 评估治疗前CT表现及血清指标预测免疫/靶向治疗对中晚期肝细胞癌（HCC）的效果的价值。方法 回顾性分析50例经穿刺活检组织病理学检查确诊的中晚期HCC患者，均于靶向/免疫治疗前和治疗8周后接受腹部CT及实验室血清检查；根据改良实体瘤疗效评价标准评价疗效，并据以分为控制组（n=40）及进展组（n=10），比较治疗前组间CT表现及血清指标差异。采用受试者工作特征（ROC）曲线确定CT征象及血清学指标预测疗效的截断值，以多因素Logistic回归分析CT征象、血清指标与疗效的关系，并建立预测模型，以ROC曲线评价其预测疗效的效能。结果 组间HCC最大截面面积、是否邻近肝包膜及血小板计数、白蛋白/纤维蛋白原（AFR）差异均有统计学意义（P均<0.05）；最大截面面积、静脉期强化率、血小板计数为预测疗效的独立因素（P均<0.05）。联合预测模型、CT征象预测模型及血清指标预测模型的AUC分别为0.88、0.81及0.71（P均>0.05）。结论 根据治疗前CT表现及血清学指标均可预测免疫/靶向治疗对中晚期HCC的效果；联合应用上述指标或可提高预测效能。

CT manifestations and serum indexes for predicting efficacy of immune/targeted therapy for advanced hepatocellular carcinoma

Objective To observe the value of pre-treatment CT manifestations and serum indexes for predicting the efficacy of immune/targeted therapy for advanced hepatocellular carcinoma (HCC). Methods Abdominal CT before targeted/immunotherapy and 8 weeks after treatment, as well as pre-treatment laboratory serum data of 50 patients with advanced HCC proved pathologically were retrospectively analyzed. According to the modified response evaluation criteria of solid tumors standard, then patients were divided into control group (n=40) and progressive group (n=10). CT manifestations and serum indexes before treatment were compared between groups. Receiver operating characteristic (ROC) curve was used to assess the cut-off value of CT manifestations and serum indexes for predicting the therapeutic efficacy of HCC, and multi-factor Logistic regression was used to analyze the relationships of CT manifestations and serum indexes and the therapeutic efficacy of HCC, and the corresponding prediction models were established. ROC curve was used to evaluate the efficacy of each model in predicting efficacy of HCC. Results There were statistical differences of the maximum cross-sectional areas, adjacent liver capsule, platelet count and albumin-fibrinogen ratio (AFR) between groups (all P<0.05), and the maximum cross-sectional area, venous enhancement rate and platelet count were independent predictors of efficacy (all P<0.05). AUC of the combined prediction model, CT and the serum indexes model was 0.88, 0.81 and 0.71, respectively (all P>0.05), while the diagnostic specificity of the combined model was higher than that of CT, and the sensitivity was higher than that of the serum indexes model. Conclusion Both CT manifestations and serum indexes before immune/targeted therapy were helpful to predict the treatment effect of advanced HCC, and the combination of the above might be benefit to improve the predicting efficacy.