Ren Zhihui, He Shasha, Fan Xiaotang, He Fangping, Sang Wei, Bao Yongxing, Ren Weixin, Zhao Jinming, Ji Xuewen, Wen Hao
Clinical Medicine Research Institute Department of Hepatology Department of Pathology Cancer Center Department of Interventional Radiology Department of Laparoscopic Surgery of Liver Department of Hepatobiliary Surgery, the First Affiliated Hospital of Xinjiang Medical University, Urumqi, People's Republic of China.
Medicine (Baltimore). 2017 Sep;96(37):e7902. doi: 10.1097/MD.0000000000007902.
This study is to establish a predictive index (PI) model of 5-year survival rate for patients with hepatocellular carcinoma (HCC) after radical resection and to evaluate its prediction sensitivity, specificity, and accuracy.Patients underwent HCC surgical resection were enrolled and randomly divided into prediction model group (101 patients) and model evaluation group (100 patients). Cox regression model was used for univariate and multivariate survival analysis. A PI model was established based on multivariate analysis and receiver operating characteristic (ROC) curve was drawn accordingly. The area under ROC (AUROC) and PI cutoff value was identified.Multiple Cox regression analysis of prediction model group showed that neutrophil to lymphocyte ratio, histological grade, microvascular invasion, positive resection margin, number of tumor, and postoperative transcatheter arterial chemoembolization treatment were the independent predictors for the 5-year survival rate for HCC patients. The model was PI = 0.377 × NLR + 0.554 × HG + 0.927 × PRM + 0.778 × MVI + 0.740 × NT - 0.831 × transcatheter arterial chemoembolization (TACE). In the prediction model group, AUROC was 0.832 and the PI cutoff value was 3.38. The sensitivity, specificity, and accuracy were 78.0%, 80%, and 79.2%, respectively. In model evaluation group, AUROC was 0.822, and the PI cutoff value was well corresponded to the prediction model group with sensitivity, specificity, and accuracy of 85.0%, 83.3%, and 84.0%, respectively.The PI model can quantify the mortality risk of hepatitis B related HCC with high sensitivity, specificity, and accuracy.
本研究旨在建立肝细胞癌（HCC）患者根治性切除术后5年生存率的预测指数（PI）模型，并评估其预测敏感性、特异性和准确性。纳入接受HCC手术切除的患者，并随机分为预测模型组（101例患者）和模型评估组（100例患者）。采用Cox回归模型进行单因素和多因素生存分析。基于多因素分析建立PI模型，并据此绘制受试者工作特征（ROC）曲线。确定ROC曲线下面积（AUROC）和PI临界值。预测模型组的多因素Cox回归分析显示，中性粒细胞与淋巴细胞比值、组织学分级、微血管侵犯、手术切缘阳性、肿瘤数量和术后经动脉化疗栓塞治疗是HCC患者5年生存率的独立预测因素。该模型为PI = 0.377×中性粒细胞与淋巴细胞比值 + 0.554×组织学分级 + 0.927×手术切缘阳性 + 0.778×微血管侵犯 + 0.740×肿瘤数量 - 0.831×经动脉化疗栓塞（TACE）。在预测模型组中，AUROC为0.832，PI临界值为3.38。敏感性、特异性和准确性分别为78.0%、80%和79.2%。在模型评估组中，AUROC为0.822，PI临界值与预测模型组吻合良好，敏感性、特异性和准确性分别为85.0%、83.3%和84.0%。PI模型能够以高敏感性、特异性和准确性量化乙型肝炎相关HCC的死亡风险。
