Liu Yue, Jiang Wenrong, Li Xiangxiao, Zhao Hu, Wang Shiwen
Department of Laboratory Medicine, Huadong Hospital, Fudan University, Shanghai, People's Republic of China.
J Hepatocell Carcinoma. 2025 Mar 6;12:513-526. doi: 10.2147/JHC.S499966. eCollection 2025.
The prevalence of primary liver cancer (PLC) is rising, yet strategies for its early diagnosis remain inadequate. This study aims to identify novel biomarkers to improve the diagnostic ability of PLC.
This study included 94 patients with PLC, 128 patients with benign liver disease (BLD), and 79 normal controls (NC) were included. Among the PLC group, there were 39 patients with hepatocellular carcinoma (HCC), 14 patients with intrahepatic cholangiocarcinoma (ICC), 4 patients with combined hepatocellular-cholangiocarcinoma (CHC) and 37 patients with imaging-diagnosed HCC, respectively. Serum biomarkers and other laboratory parameters were collected and analyzed. Diagnostic values of individual and combined biomarkers for PLC were assessed using receiver operating characteristic (ROC) curve analysis. Univariate and multivariate logistic regression identified predictors of PLC, and a nomogram model was developed based on the independent predictors.
AFP and DCP levels were significantly higher in the HCC patients compared to those with the BLD. AFP-L3 and CA199 levels were markedly elevated in patients with HCC, ICC, and CHC compared with the other groups. Combining AFP, AFP-L3, DCP, and CA199 increased the AUC to 0.8492 for the PLC group versus the BLD group. Multivariate logistic regression analysis identified sex, AFP-L3, DCP, and CA199 as independent predictors of PLC, and a reliable nomogram model was developed based on these predictors.
The combined use of AFP, AFP-L3, DCP, and CA199 significantly enhanced the diagnostic performance of PLC compared with existing models like GALAD (gender, age, AFP, AFP-L3, and DCP), and ASAP (age, sex, AFP, DCP), as well as individual biomarkers.
原发性肝癌(PLC)的患病率正在上升,但其早期诊断策略仍不完善。本研究旨在识别新的生物标志物,以提高PLC的诊断能力。
本研究纳入了94例PLC患者、128例良性肝病(BLD)患者和79例正常对照(NC)。在PLC组中,分别有39例肝细胞癌(HCC)患者、14例肝内胆管癌(ICC)患者、4例肝细胞-胆管癌(CHC)患者和37例影像诊断为HCC的患者。收集并分析血清生物标志物和其他实验室参数。使用受试者工作特征(ROC)曲线分析评估单个和联合生物标志物对PLC的诊断价值。单因素和多因素逻辑回归确定PLC的预测因素,并基于独立预测因素建立列线图模型。
与BLD患者相比,HCC患者的甲胎蛋白(AFP)和异常凝血酶原(DCP)水平显著更高。与其他组相比,HCC、ICC和CHC患者的AFP异质体-L3(AFP-L3)和糖类抗原199(CA199)水平显著升高。将AFP、AFP-L3、DCP和CA199联合使用,使PLC组与BLD组相比的曲线下面积(AUC)提高到0.8492。多因素逻辑回归分析确定性别、AFP-L3、DCP和CA199为PLC的独立预测因素,并基于这些预测因素建立了可靠的列线图模型。
与现有模型如GALAD(性别、年龄、AFP、AFP-L3和DCP)、ASAP(年龄、性别、AFP、DCP)以及单个生物标志物相比,联合使用AFP、AFP-L3、DCP和CA199显著提高了PLC的诊断性能。