Cai Zhi-Qiang, Si Shu-Bin, Chen Chen, Zhao Yaling, Ma Yong-Yi, Wang Lin, Geng Zhi-Min
Department of Hepatobiliary Surgery, First Affiliated Hospital of Xi'an Jiaotong University, College of Medicine, Xi'an 710061, Shaanxi, China; Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, China.
Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, China.
PLoS One. 2015 Mar 31;10(3):e0120805. doi: 10.1371/journal.pone.0120805. eCollection 2015.
The prognosis of hepatocellular carcinoma (HCC) after hepatectomy involves many factors. Previous studies have evaluated the separate influences of single factors; few have considered the combined influence of various factors. This paper combines the Bayesian network (BN) with importance measures to identify key factors that have significant effects on survival time.
A dataset of 299 patients with HCC after hepatectomy was studied to establish a BN using a tree-augmented naïve Bayes algorithm that could mine relationships between factors. The composite importance measure was applied to rank the impact of factors on survival time.
124 patients (>10 months) and 77 patients (≤10 months) were correctly classified. The accuracy of BN model was 67.2%. For patients with long survival time (>10 months), the true-positive rate of the model was 83.22% and the false-positive rate was 48.67%. According to the model, the preoperative alpha fetoprotein (AFP) level and postoperative performance of transcatheter arterial chemoembolization (TACE) were independent factors for survival of HCC patients. The grade of preoperative liver function reflected the tendency for postoperative complications. Intraoperative blood loss, tumor size, portal vein tumor thrombosis (PVTT), time of clamping the porta hepatis, tumor number, operative method, and metastasis were dependent variables in survival time prediction. PVTT was considered the most significant for the prognosis of survival time.
Using the BN and importance measures, PVTT was identified as the most significant predictor of survival time for patients with HCC after hepatectomy.
肝切除术后肝细胞癌（HCC）的预后涉及多种因素。以往研究评估了单一因素的单独影响；很少有研究考虑多种因素的综合影响。本文将贝叶斯网络（BN）与重要性度量相结合，以识别对生存时间有显著影响的关键因素。
研究了299例肝切除术后HCC患者的数据集，使用树增强朴素贝叶斯算法建立BN，该算法可以挖掘因素之间的关系。应用综合重要性度量对因素对生存时间的影响进行排序。
124例（>10个月）和77例（≤10个月）患者被正确分类。BN模型的准确率为67.2%。对于生存时间长（>10个月）的患者，模型的真阳性率为83.22%，假阳性率为48.67%。根据该模型，术前甲胎蛋白（AFP）水平和经动脉化疗栓塞术（TACE）的术后表现是HCC患者生存的独立因素。术前肝功能分级反映了术后并发症的发生趋势。术中出血量、肿瘤大小、门静脉癌栓（PVTT）、肝门阻断时间、肿瘤数量、手术方式和转移是生存时间预测中的因变量。PVTT被认为对生存时间的预后影响最大。
使用BN和重要性度量，PVTT被确定为肝切除术后HCC患者生存时间的最显著预测因素。
