Liu Long, Wang Qi, Zhao Xiaohong, Huang Yuxi, Feng Yuyi, Zhang Yu, Fang Zheping, Li Shaowei
Department of Hepatobiliary Surgery, Taizhou Hospital of Zhejiang Province, Zhejiang University, Linhai, Zhejiang, China.
Department of Hepatobiliary Surgery, Taizhou Hospital of Zhejiang Province, Wenzhou Medical University, Linhai, Zhejiang, China.
Front Oncol. 2023 Feb 20;13:1131892. doi: 10.3389/fonc.2023.1131892. eCollection 2023.
As one of the most common malignant tumors in clinical practice, hepatocellular carcinoma (HCC) is a major threat to human health, where alpha-fetoprotein (AFP) is widely used for early screening and diagnoses. However, the level of AFP would not elevate in about 30-40% of HCC patients, which is clinically referred to as AFP-negative HCC, with small tumors at an early stage and atypical imaging features, making it difficult to distinguish benign from malignant by imaging alone.
A total of 798 patients, with the majority being HBV-positive, were enrolled in the study and were randomized 2:1 to the training and validation groups. Univariate and multivariate binary logistic regression analyses were used to determine the ability of each parameter to predict HCC. A nomogram model was constructed based on the independent predictors.
A unordered multicategorical logistic regression analyses showed that the age, TBIL, ALT, ALB, PT, GGT and GPR help identify non-hepatic disease, hepatitis, cirrhosis, and hepatocellular carcinoma. A multivariate logistic regression analyses showed that the gender, age, TBIL, GAR, and GPR were independent predictors for the diagnosis of AFP-negative HCC. And an efficient and reliable nomogram model (AUC=0.837) was constructed based on independent predictors.
Serum parameters help reveal intrinsic differences between non-hepatic disease, hepatitis, cirrhosis, and HCC. The nomogram based on clinical and serum parameters could be used as a marker for the diagnosis of AFP-negative HCC, providing an objective basis for the early diagnosis and individualized treatment of hepatocellular carcinoma patients.
作为临床实践中最常见的恶性肿瘤之一，肝细胞癌（HCC）对人类健康构成重大威胁，甲胎蛋白（AFP）被广泛用于早期筛查和诊断。然而，约30%-40%的HCC患者AFP水平不会升高，临床上称为AFP阴性HCC，其肿瘤早期较小且具有非典型影像学特征，仅靠影像学难以区分良恶性。
本研究共纳入798例患者，多数为乙肝病毒阳性，按2:1随机分为训练组和验证组。采用单因素和多因素二元逻辑回归分析确定各参数预测HCC的能力。基于独立预测因子构建列线图模型。
无序多分类逻辑回归分析显示，年龄、总胆红素（TBIL）、谷丙转氨酶（ALT）、白蛋白（ALB）、凝血酶原时间（PT）、γ-谷氨酰转肽酶（GGT）和甘氨酰脯氨酸二肽氨基肽酶（GPR）有助于识别非肝脏疾病、肝炎、肝硬化和肝细胞癌。多因素逻辑回归分析显示，性别、年龄、TBIL、GAR和GPR是诊断AFP阴性HCC的独立预测因子。并基于独立预测因子构建了一个高效可靠的列线图模型（曲线下面积[AUC]=0.837）。
血清参数有助于揭示非肝脏疾病、肝炎、肝硬化和HCC之间的内在差异。基于临床和血清参数的列线图可作为AFP阴性HCC诊断的标志物，为肝细胞癌患者的早期诊断和个体化治疗提供客观依据。
