Jun-Cheng Wang1, Jing-Yu Hou1, Jian-Cong Chen2, Cai-Ling Xiang3, Xian-Hai Mao4, Bing Yang5, Qiang Li6, Qing-Bo Liu7, Jinbin Chen1, Zhi-Wei Ye1, Wei Peng1, Xu-Qi Sun1, Min-Shan Chen8, Qun-Fang Zhou9, Yao-Jun Zhang10. 1. Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, PR China; Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060, PR China. 2. Department of Pancreato-Biliary Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, PR China. 3. Department of General Surgery, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University) Changsha, 410002, Hunan province, China. 4. Department of Hepatobiliary Surgery, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University) Changsha, 410002, Hunan province, China. 5. Department of Neurology and Stroke Center, The First Affiliated Hospital, Jinan University, Guangzhou, 510632, China. 6. Department of General Surgery, The First Affiliated Hospital, Jinan University, Guangzhou, 510630, China. 7. Department of Hepatobiliary Surgery, Shunde Hospital, Southern Medical University, Foshan, 528308, Guangdong province, China. 8. Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, PR China; Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060, PR China. Electronic address: chenmsh@sysucc.org.cn. 9. Department of Minimally Invasive Interventional Radiology, Department of Radiology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, China. Electronic address: zhouqun988509@163.com. 10. Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, PR China; Department of Liver Surgery, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060, PR China. Electronic address: zhangyuj@sysucc.org.cn.
Abstract
AIM: The prediction model of postoperative survival for single large and huge hepatocellular carcinoma (SLH-HCC, diameter > 5.0 cm) without portal vein tumour thrombus has not been well established. This study aimed to develop novel nomograms to predict postoperative recurrence and survival of these patients. METHODS: Data from 2469 patients with SLH-HCC who underwent curative resection from January 2005 to December 2015 in China were retrospectively collected. Specifically, nomograms of recurrence-free survival (RFS) and overall survival (OS) using data from a training cohort were developed with the Cox regression model (n = 1012). The modes were verified in an internal validation cohort (n = 338) and an external cohort comprising four tertiary institutions (n = 1119). RESULTS: The nomograms of RFS and OS based on tumour clinicopathologic features (diameter, differentiation, microvascular invasion, α-fetoprotein), operative factors (preoperative transcatheter arterial chemoembolisation therapy, scope of liver resection and intraoperative blood transfusion), underlying liver function (albumin-bilirubin grade) and systemic inflammatory or immune status (neutrophil-to-lymphocyte ratio) achieved high C-indexes of 0.85 (95% confidence interval [CI], 0.79-0.91) and 0.86 (95% CI, 0.79-0.93) in the training cohort, respectively, which were significantly higher than those of the five conventional HCC staging systems (0.62-0.73 for RFS, 0.63-0.75 for OS). The nomograms were validated in the internal cohort (0.83 for RFS, 0.84 for OS) and external cohort (0.87 for RFS, 0.88 for OS) and had well-fitted calibration curves. Our nomograms accurately stratified patients with SLH-HCC into low-, intermediate- and high-risk groups of postsurgical recurrence and mortality. CONCLUSIONS: The two nomograms achieved optimal prediction for postsurgical recurrence and OS for patients with SLH-HCC after curative resection.
AIM: The prediction model of postoperative survival for single large and huge hepatocellular carcinoma (SLH-HCC, diameter > 5.0 cm) without portal vein tumour thrombus has not been well established. This study aimed to develop novel nomograms to predict postoperative recurrence and survival of these patients. METHODS: Data from 2469 patients with SLH-HCC who underwent curative resection from January 2005 to December 2015 in China were retrospectively collected. Specifically, nomograms of recurrence-free survival (RFS) and overall survival (OS) using data from a training cohort were developed with the Cox regression model (n = 1012). The modes were verified in an internal validation cohort (n = 338) and an external cohort comprising four tertiary institutions (n = 1119). RESULTS: The nomograms of RFS and OS based on tumour clinicopathologic features (diameter, differentiation, microvascular invasion, α-fetoprotein), operative factors (preoperative transcatheter arterial chemoembolisation therapy, scope of liver resection and intraoperative blood transfusion), underlying liver function (albumin-bilirubin grade) and systemic inflammatory or immune status (neutrophil-to-lymphocyte ratio) achieved high C-indexes of 0.85 (95% confidence interval [CI], 0.79-0.91) and 0.86 (95% CI, 0.79-0.93) in the training cohort, respectively, which were significantly higher than those of the five conventional HCC staging systems (0.62-0.73 for RFS, 0.63-0.75 for OS). The nomograms were validated in the internal cohort (0.83 for RFS, 0.84 for OS) and external cohort (0.87 for RFS, 0.88 for OS) and had well-fitted calibration curves. Our nomograms accurately stratified patients with SLH-HCC into low-, intermediate- and high-risk groups of postsurgical recurrence and mortality. CONCLUSIONS: The two nomograms achieved optimal prediction for postsurgical recurrence and OS for patients with SLH-HCC after curative resection.