OBJECTIVE: 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 survival (RFS) of high-risk groups were significantly lower than those of low- and middle-risk groups (P < 0.001). The DCA shows that the model has better clinical practicability.
CONCLUSIONS: The study developed a predictive nomogram based on TTD, VI, AFP, and CK18-M30 that could accurately predict overall survival and RFS after LT. It can screen for patients with better postoperative prognosis, and improve long-term survival for LT patients.
目的:建立预测肝癌患者肝移植后预后的模型。
方法:收集并评估了160例接受LT的HCC患者的临床数据和随访信息。甲胎蛋白(AFP)的表达水平,des-γ-羧基凝血酶原,使用全自动化学发光分析仪测量高尔基体蛋白73,细胞角蛋白18表位M30和M65。使用Youden指数确定生物标志物的最佳截止值。采用Cox回归分析确定独立危险因素。使用随机森林方法构建了森林模型。我们使用曲线下的面积来评估列线图的准确性,使用校准曲线评估一致性。使用决策曲线分析(DCA)来评价列线图的临床效用。
结果:肿瘤总直径(TTD),血管浸润(VI),法新社,和细胞角蛋白18表位M30(CK18-M30)被确定为LT后结局的重要危险因素。列线图比米兰有更高的预测准确性,加州大学,旧金山,和杭州标准。校准曲线分析表明良好的拟合。高危组患者的生存率和无复发生存率(RFS)明显低于低危组和中危组(P<0.001)。DCA表明该模型具有较好的临床实用性。
结论:该研究开发了基于TTD的预测列线图,VI,法新社,CK18-M30可以准确预测LT术后总生存率和RFS。它可以筛选术后预后较好的患者,并提高LT患者的长期生存率。