在美国，肝细胞癌 (HCC) 是自 1980 年以来增长最快的癌症，代谢功能障碍相关的脂肪肝病 (MASLD) 预计将很快成为 HCC 的主要原因。一组 MASLD 患者。这项预后研究是在年龄至少 18 岁的 MASLD 患者中进行的，这些患者是使用国际疾病分类第九版修订版 (ICD-9) 或国际疾病和相关健康问题统计分类诊断 MASLD 来确定的，第十次修订（ICD-10）诊断代码；放射影像报告文本的自然语言处理，识别出具有 MASLD 影像证据但尚未正式诊断的患者；或达拉斯脂肪变性指数，这是一个风险方程，可以高精度识别可能患有 MASLD 的个体。患者从北加州 Kaiser Permanente 入组，该系统是一个拥有超过 460 万名会员的综合医疗服务系统，于 2009 年 1 月至 2018 年 12 月期间进入研究，并随访直至 2021 年 9 月 30 日发生 HCC、死亡或研究终止。统计分析于 2023 年 2 月和 2024 年 1 月期间进行。数据从电子健康记录中提取，包括 18 个与 MASLD 相关的常规测量因素。队列被分为 (70:30) 推导集和内部验证集；使用极端梯度增强来模拟 HCC 发病率。 HCC风险分为3类，HCC累积估计概率0.05%以下为低风险； 0.05%至0.09%，中等风险； 0.1%或更高，高风险。共有1811461名患者（基线时中位年龄[IQR]，52[41-63]岁；982300[54.2%]女性）参与了该研究。在中位（范围）9.3（5.8-12.4）年的随访期间，946 名患者发展为 HCC，发病率为每 1000 人年 0.065 例。该模型在验证集中实现了 0.899 的曲线下面积（95% CI，0.882-0.916）。在中等风险阈值下，模型的敏感性为87.5%，特异性为81.4%，需要筛选的数量为406。在高风险阈值下，模型的敏感性为78.4%，特异性为90.1 %，需要筛查的人数为 241。这项针对超过 180 万 MASLD 患者的预后研究使用电子健康记录数据开发了一个预测模型，能够以良好的精度区分患有和未患 HCC 的个体。该模型可以作为识别可能需要干预和/或 HCC 监测的 MASLD 患者的起点。

In the US, hepatocellular carcinoma (HCC) has been the most rapidly increasing cancer since 1980, and metabolic dysfunction-associated steatotic liver disease (MASLD) is expected to soon become the leading cause of HCC.To develop a prediction model for HCC incidence in a cohort of patients with MASLD.This prognostic study was conducted among patients aged at least 18 years with MASLD, identified using diagnosis of MASLD using International Classification of Diseases, Ninth Revision (ICD-9) or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) diagnosis codes; natural language processing of radiology imaging report text, which identified patients who had imaging evidence of MASLD but had not been formally diagnosed; or the Dallas Steatosis Index, a risk equation that identifies individuals likely to have MASLD with good precision. Patients were enrolled from Kaiser Permanente Northern California, an integrated health delivery system with more than 4.6 million members, with study entry between January 2009 and December 2018, and follow-up until HCC development, death, or study termination on September 30, 2021. Statistical analysis was performed during February 2023 and January 2024.Data were extracted from the electronic health record and included 18 routinely measured factors associated with MASLD.The cohort was split (70:30) into derivation and internal validation sets; extreme gradient boosting was used to model HCC incidence. HCC risk was divided into 3 categories, with the cumulative estimated probability of HCC 0.05% or less classified as low risk; 0.05% to 0.09%, medium risk; and 0.1% or greater, high risk.A total of 1 811 461 patients (median age [IQR] at baseline, 52 [41-63] years; 982 300 [54.2%] female) participated in the study. During a median (range) follow-up of 9.3 (5.8-12.4) years, 946 patients developed HCC, for an incidence rate of 0.065 per 1000 person-years. The model achieved an area under the curve of 0.899 (95% CI, 0.882-0.916) in the validation set. At the medium-risk threshold, the model had a sensitivity of 87.5%, specificity of 81.4%, and a number needed to screen of 406. At the high-risk threshold, the model had a sensitivity of 78.4%, a specificity of 90.1%, and a number needed to screen of 241.This prognostic study of more than 1.8 million patients with MASLD used electronic health record data to develop a prediction model to discriminate between individuals with and without incident HCC with good precision. This model could serve as a starting point to identify patients with MASLD who may need intervention and/or HCC surveillance.