Cao Qunmei, Zhou Yilin, Wen Changlong, Li Qinglan
Department of Infectious Disease, Ganzhou People's Hospital, Ganzhou, China.
Epidemiol Infect. 2025 Sep 16;153:e111. doi: 10.1017/S0950268825100538.
A predictive column chart was developed to assess the risk of primary liver cancer (PLC) in hepatitis B patients. Data from 107 PLC patients and 107 controls were used as the training set, with 92 patients as the validation set. An additional 446 patients from other hospitals, including 15 with PLC, formed the external validation group. Multivariate logistic regression identified gender, BMI, alcohol consumption, diabetes, family history of liver cancer, cirrhosis, and HBV DNA load as independent risk factors. The model showed strong discrimination with AUCs of 0.882 and 0.859 in the training and validation sets, respectively, and good calibration (Hosmer-Lemeshow χ² = 2.648, P = 0.954; χ² = 4.117, P = 0.846). Decision curve analysis (DCA) confirmed clinical benefit within a risk threshold of 0.07-0.95. In the external validation group, the model maintained discrimination (AUC = 0.863) and calibration (Hosmer-Lemeshow χ² = 7.999, P = 0.434), with DCA showing net benefit across 0.14-0.95. These results indicate the column chart is a reliable tool for PLC risk prediction in hepatitis B patients.
开发了一种预测性柱状图来评估乙肝患者原发性肝癌（PLC）的风险。来自107例PLC患者和107例对照的数据用作训练集，92例患者作为验证集。来自其他医院的另外446例患者，包括15例PLC患者，组成了外部验证组。多变量逻辑回归确定性别、体重指数、饮酒、糖尿病、肝癌家族史、肝硬化和HBV DNA载量为独立危险因素。该模型在训练集和验证集中分别显示出较强的区分度，AUC分别为0.882和0.859，且校准良好（Hosmer-Lemeshow χ² = 2.648，P = 0.954；χ² = 4.117，P = 0.846）。决策曲线分析（DCA）证实在0.07-0.95的风险阈值内具有临床益处。在外部验证组中，该模型保持了区分度（AUC = 0.863）和校准（Hosmer-Lemeshow χ² = 7.999，P = 0.434），DCA显示在0.14-0.95范围内有净效益。这些结果表明，该柱状图是预测乙肝患者PLC风险的可靠工具。
