Mitchell Natasha D P, Pierre Timothy G St, Ramm Louise E, Ramm Grant A, Olynyk John K
Department of Gastroenterology, Fiona Stanley Hospital, Murdoch, WA, Australia.
School of Physics, Mathematics, and Computing, The University of Western Australia, Perth, WA, Australia.
Sci Rep. 2025 May 8;15(1):16011. doi: 10.1038/s41598-025-99672-8.
HFE hemochromatosis (HH) may cause cirrhosis and hepatocellular carcinoma (HCC). Progression to these endpoints depends on the severity of iron overload and cofactors, such as alcohol. We evaluated alcohol and iron-related risk factors in relation to cirrhosis at diagnosis and future development of HCC in a retrospective analysis of 197 HH subjects. The proportion of subjects either with cirrhosis or who developed HCC during follow-up were 29/197 (14.7%) or 10/197 (5.1%), respectively. The median (IQR) follow-up time after diagnosis was 15.2 (4.6 to 22.1) years. The median mobilizable iron stores and daily alcohol consumption (IQR) were 6.0 (3.8-11.0) g and 20 (0-40) g, respectively. An optimal logistic regression model for the odds of cirrhosis was developed by adding candidate liver insult variables (mobilizable iron, alcohol consumption, and age as a surrogate for duration of exposure) in a forward stepwise strategy using area under the receiver operating characteristic curve (AUROC) analysis and the corrected Akaike information criterion. This model demonstrated an AUROC (95% CI) of 0.966 (0.935-0.996), with sensitivity 76 (58-88)% and specificity 97 (93-99) % for prediction of cirrhosis and had a negative predictive value of 99.4 (95% CI 96.7-99.97) % for development of HCC. Thus, future risk of HCC can be assessed from mobilizable iron stores and alcohol consumption of HH subjects.
HFE 遗传性血色素沉着症（HH）可能导致肝硬化和肝细胞癌（HCC）。疾病进展至这些终点取决于铁过载的严重程度以及酒精等辅助因素。我们在一项对 197 名 HH 受试者的回顾性分析中，评估了与诊断时的肝硬化以及未来 HCC 发生相关的酒精和铁相关危险因素。随访期间出现肝硬化或发生 HCC 的受试者比例分别为 29/197（14.7%）和 10/197（5.1%）。诊断后的中位（四分位间距）随访时间为 15.2（4.6 至 22.1）年。可动员铁储存量的中位数和每日酒精摄入量（四分位间距）分别为 6.0（3.8 - 11.0）克和 20（0 - 40）克。通过在前向逐步策略中添加候选肝脏损伤变量（可动员铁、酒精摄入量以及作为暴露持续时间替代指标的年龄），利用受试者工作特征曲线下面积（AUROC）分析和校正后的赤池信息准则，建立了一个关于肝硬化发生几率的最佳逻辑回归模型。该模型预测肝硬化的 AUROC（95%可信区间）为 0.966（0.935 - 0.996），敏感性为 76（58 - 88）%，特异性为 97（93 - 99）%，对 HCC 发生的阴性预测值为 99.4（95%可信区间 96.7 - 99.97）%。因此，可以根据 HH 受试者的可动员铁储存量和酒精摄入量来评估未来发生 HCC 的风险。
