Lei Liang1,2, Bing Quan3, Han Wu4, Yong-Kang Diao1,2, Jie Li5, Ting-Hao Chen6, Yao-Ming Zhang7, Ya-Hao Zhou8, Wan-Guang Zhang9, Hong Wang10, Matteo Serenari11, Matteo Cescon11, Myron Schwartz12, Yong-Yi Zeng13, Ying-Jian Liang14, Hang-Dong Jia1,2, Hao Xing4, Chao Li4, Ming-Da Wang4, Wen-Tao Yan3, Wan-Yuan Chen15, Wan Yee Lau4,16, Cheng-Wu Zhang1, Timothy M Pawlik17, Dong-Sheng Huang18,19, Feng Shen4, Tian Yang20,21,22. 1. Department of Hepatobiliary, Pancreatic and Minimal Invasive Surgery, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Zhejiang, China. 2. Hepatobiliary Cancer Institute, Hangzhou Medical College, Hangzhou, Zhejiang, China. 3. Department of Clinical Medicine, Second Military Medical University (Navy Medical University), Shanghai, China. 4. Department of Hepatobiliary Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University (Navy Medical University), Shanghai, China. 5. Department of Hepatobiliary Surgery, Fuyang People's Hospital, Anhui, China. 6. Department of General Surgery, Ziyang First People's Hospital, Sichuan, China. 7. The second Department of Hepatobiliary Surgery, Meizhou People's Hospital, Guangdong, China. 8. Department of Hepatobiliary Surgery, Pu'er People's Hospital, Yunnan, China. 9. Department of Hepatic Surgery, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China. 10. Department of General Surgery, Liuyang People's Hospital, Hunan, China. 11. Department of Medical and Surgical Sciences, General Surgery and Transplantation Unit, University of Bologna, Bologna, Italy. 12. Liver Cancer Program, Recanati/Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. 13. Department of Hepatobiliary Surgery, Mengchao Hepatobiliary Hospital, Fujian Medical University, Fujian, China. 14. Department of Hepatobiliary Surgery, The First Affiliated Hospital of Harbin Medical University, Heilongjiang, China. 15. Department of Pathology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Zhejiang, China. 16. Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China. 17. Department of Surgery, Ohio State University, Wexner Medical Center, Columbus, OH, USA. 18. Department of Hepatobiliary, Pancreatic and Minimal Invasive Surgery, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Zhejiang, China. Huangdongshengsj@hotmail.com. 19. Hepatobiliary Cancer Institute, Hangzhou Medical College, Hangzhou, Zhejiang, China. Huangdongshengsj@hotmail.com. 20. Department of Hepatobiliary, Pancreatic and Minimal Invasive Surgery, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Zhejiang, China. yangtiandfgd@hotmail.com. 21. Department of Hepatobiliary Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University (Navy Medical University), Shanghai, China. yangtiandfgd@hotmail.com. 22. Hepatobiliary Cancer Institute, Hangzhou Medical College, Hangzhou, Zhejiang, China. yangtiandfgd@hotmail.com.
Abstract
BACKGROUND: Evidence-based decision-making is critical to optimize the benefits and mitigate futility associated with surgery for patients with malignancies. Untreated hepatocellular carcinoma (HCC) has a median survival of only 6 months. The objective was to develop and validate an individualized patient-specific tool to predict preoperatively the benefit of surgery to provide a survival benefit of at least 6 months following resection. METHODS: Using an international multicenter database, patients who underwent curative-intent liver resection for HCC from 2008 to 2017 were identified. Using random assignment, two-thirds of patients were assigned to a training cohort with the remaining one-third assigned to the validation cohort. Independent predictors of postoperative death within 6 months after surgery for HCC were identified and used to construct a nomogram model with a corresponding online calculator. The predictive accuracy of the calculator was assessed using C-index and calibration curves. RESULTS: Independent factors associated with death within 6 months of surgery included age, Child-Pugh grading, portal hypertension, alpha-fetoprotein level, tumor rupture, tumor size, tumor number and gross vascular invasion. A nomogram that incorporated these factors demonstrated excellent calibration and good performance in both the training and validation cohorts (C-indexes: 0.802 and 0.798). The nomogram also performed better than four other commonly-used HCC staging systems (C-indexes: 0.800 vs. 0.542-0.748). CONCLUSIONS: An easy-to-use online prediction calculator was able to identify patients at highest risk of death within 6 months of surgery for HCC. The proposed online calculator may help guide surgical decision-making to avoid futile surgery for patients with HCC.
BACKGROUND: Evidence-based decision-making is critical to optimize the benefits and mitigate futility associated with surgery for patients with malignancies. Untreated hepatocellular carcinoma (HCC) has a median survival of only 6 months. The objective was to develop and validate an individualized patient-specific tool to predict preoperatively the benefit of surgery to provide a survival benefit of at least 6 months following resection. METHODS: Using an international multicenter database, patients who underwent curative-intent liver resection for HCC from 2008 to 2017 were identified. Using random assignment, two-thirds of patients were assigned to a training cohort with the remaining one-third assigned to the validation cohort. Independent predictors of postoperative death within 6 months after surgery for HCC were identified and used to construct a nomogram model with a corresponding online calculator. The predictive accuracy of the calculator was assessed using C-index and calibration curves. RESULTS: Independent factors associated with death within 6 months of surgery included age, Child-Pugh grading, portal hypertension, alpha-fetoprotein level, tumor rupture, tumor size, tumor number and gross vascular invasion. A nomogram that incorporated these factors demonstrated excellent calibration and good performance in both the training and validation cohorts (C-indexes: 0.802 and 0.798). The nomogram also performed better than four other commonly-used HCC staging systems (C-indexes: 0.800 vs. 0.542-0.748). CONCLUSIONS: An easy-to-use online prediction calculator was able to identify patients at highest risk of death within 6 months of surgery for HCC. The proposed online calculator may help guide surgical decision-making to avoid futile surgery for patients with HCC.
Authors: Nuh N Rahbari; Arianeb Mehrabi; Nathan M Mollberg; Sascha A Müller; Moritz Koch; Markus W Büchler; Jürgen Weitz Journal: Ann Surg Date: 2011-03 Impact factor: 12.969
Authors: Josep M Llovet; Sergio Ricci; Vincenzo Mazzaferro; Philip Hilgard; Edward Gane; Jean-Frédéric Blanc; Andre Cosme de Oliveira; Armando Santoro; Jean-Luc Raoul; Alejandro Forner; Myron Schwartz; Camillo Porta; Stefan Zeuzem; Luigi Bolondi; Tim F Greten; Peter R Galle; Jean-François Seitz; Ivan Borbath; Dieter Häussinger; Tom Giannaris; Minghua Shan; Marius Moscovici; Dimitris Voliotis; Jordi Bruix Journal: N Engl J Med Date: 2008-07-24 Impact factor: 91.245