大多数肝癌评分系统侧重于患有慢性病毒性肝炎或肝硬化等肝脏疾病的患者。糖尿病患者患肝癌的风险高于一般人群。然而，针对无肝病或糖尿病患者的肝癌评分系统仍然很少。本研究旨在开发糖尿病患者肝癌预测的风险评分系统以及无肝硬化/慢性病毒性肝炎的糖尿病患者的子模型。利用香港的电子健康记录进行回顾性队列研究。纳入2010年至2019年期间在普通门诊接受糖尿病治疗且无癌症病史的患者，并随访至2019年12月。随访结果为肝癌。通过在变量选择中应用随机生存森林，在权重分配中应用Cox回归，开发了风险评分系统。肝癌发病率为0.92/1000人年。选择罹患肝癌的患者 (n = 1995) 和在随访期间（中位数：6.2 年）未患癌症的患者 (n = 1969) 进行模型构建。在最终的事件发生时间评分系统中，慢性乙型/丙型肝炎、丙氨酸转氨酶、年龄、肝硬化和性别均被纳入预测因素。一致性指数为0.706（95%CI：0.676-0.741）。在无肝硬化/慢性病毒性肝炎患者的子模型中，选择丙氨酸氨基转移酶、年龄、甘油三酯和性别作为预测因子。所提出的评分系统可以为糖尿病患者中肝癌风险预测提供简约的评分。

Most liver cancer scoring systems focus on patients with preexisting liver diseases such as chronic viral hepatitis or liver cirrhosis. Patients with diabetes are at higher risk of developing liver cancer than the general population. However, liver cancer scoring systems for patients in the absence of liver diseases or those with diabetes remain rare. This study aims to develop a risk scoring system for liver cancer prediction among diabetes patients and a sub-model among diabetes patients without cirrhosis/chronic viral hepatitis.A retrospective cohort study was performed using electronic health records of Hong Kong. Patients who received diabetes care in general outpatient clinics between 2010 and 2019 without cancer history were included and followed up until December 2019. The outcome was diagnosis of liver cancer during follow-up. A risk scoring system was developed by applying random survival forest in variable selection, and Cox regression in weight assignment.The liver cancer incidence was 0.92 per 1000 person-years. Patients who developed liver cancer (n = 1995) and those who remained free of cancer (n = 1969) during follow-up (median: 6.2 years) were selected for model building. In the final time-to-event scoring system, presence of chronic hepatitis B/C, alanine aminotransferase, age, presence of cirrhosis, and sex were included as predictors. The concordance index was 0.706 (95%CI: 0.676-0.741). In the sub-model for patients without cirrhosis/chronic viral hepatitis, alanine aminotransferase, age, triglycerides, and sex were selected as predictors.The proposed scoring system may provide a parsimonious score for liver cancer risk prediction among diabetes patients.