Development of a nomogram for predicting liver transplantation prognosis in hepatocellular carcinoma

作者：He Li, Wan-Sheng Ji, Hailong Jin, LU Wen-jing, Yuanyuan Zhang, Huaguang Wang, Yu-Yu Liu, Shuang Qiu, Meng Xu, Zi-Peng Lei, Qian Zheng, Xiaoli Yang, Qing Zhang · 发表于：World Journal of Gastroenterology · 年份：2024 · DOI：10.3748/wjg.v30.i21.2763 · 被引用次数：3 · 研究领域：Hepatocellular Carcinoma Treatment and Prognosis、Organ Transplantation Techniques and Outcomes、Ferroptosis and cancer prognosis

BACKGROUND At present, liver transplantation (LT) is one of the best treatments for hepatocellular carcinoma (HCC). Accurately predicting the survival status after LT can significantly improve the survival rate after LT, and ensure the best way to make rational use of liver organs. AIM To develop a model for predicting prognosis after LT in patients with HCC. METHODS Clinical data and follow-up information of 160 patients with HCC who underwent LT were collected and evaluated. The expression levels of alpha-fetoprotein (AFP), des-gamma-carboxy prothrombin, Golgi protein 73, cytokeratin-18 epitopes M30 and M65 were measured using a fully automated chemiluminescence analyzer. The best cutoff value of biomarkers was determined using the Youden index. Cox regression analysis was used to identify the independent risk factors. A forest model was constructed using the random forest method. We evaluated the accuracy of the nomogram using the area under the curve, using the calibration curve to assess consistency. A decision curve analysis (DCA) was used to evaluate the clinical utility of the nomograms. RESULTS The total tumor diameter (TTD), vascular invasion (VI), AFP, and cytokeratin-18 epitopes M30 (CK18-M30) were identified as important risk factors for outcome after LT. The nomogram had a higher predictive accuracy than the Milan, University of California, San Francisco, and Hangzhou criteria. The calibration curve analyses indicated a good fit. The survival and recurrence-free...