Wei Dong1,2, Kai Yan3, Hua Yu1,2, Lei Huo4, Zhihong Xian1,2, Yanqing Zhao1,2, Jutang Li5, Yuchan Zhang1,2, Zhenying Cao1,2, Yong Fu3, Wenming Cong1,2, Hui Dong1,2. 1. Department of Pathology, Eastern Hepatobiliary Surgery Hospital, the Second Military Medical University, Shanghai, China. 2. Key Laboratory of Signaling Regulation and Targeting Therapy of Liver Cancer, the Second Military Medical University, Shanghai, China. 3. The Fifth Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, the Second Military Medical University, Shanghai, China. 4. Department of Radiology, Eastern Hepatobiliary Surgery Hospital, the Second Military Medical University, Shanghai, China. 5. Department of Gynaecology and Obstetrics, Tong Ren Hospital, Shanghai Jiao Tong University of Medicine, Shanghai, China.
Abstract
BACKGROUND: Predicting the long-term prognosis of individuals who experienced sorafenib treatment following partial hepatectomy due to hepatitis B virus (HBV) related hepatocellular carcinoma (HCC) is difficult. This work aims to create an effective prognostic nomogram for HBV related HCC patients who are receiving sorafenib treatment as adjuvant therapy after surgery. METHODS: A total of 233 HBV-related HCC patients treated with or without sorafenib following partial hepatectomy at the Eastern Hepatobiliary Surgery Hospital from 2008 to 2013 were matched with propensity score matching analysis. The optimal cut-off point of the overall survival (OS) factor level was determined by x-tile. The selection of indicators was based on clinical findings. The Cox regression model with an interaction term was employed for evaluating the predictive value. Using a multivariate Cox proportional hazards model, a nomogram was subsequently formulated to analyze 111 patients treated with sorafenib. The nomogram's discriminative ability and predictive accuracy were determined using the concordance index (C-index), calibration, and ROC curve. RESULTS: The matched sorafenib cohort of 111 patients and control cohort of 118 patients were analyzed. Subgroup analysis revealed that low GPC3, pERK, pAKT, serum AFP levels, without MVI, under 50 years old, male, TNM stage I/II and BCLC stage 0/A were significantly associated with a better OS in patients subjected to sorafenib treatment compared to those without sorafenib treatment after surgery. Multivariate analysis of the sorafenib cohort revealed GPC3, pERK, pAKT, serum AST, and BCLC stage as independent factors for OS, and all were included in the nomogram. The survival probability based on the calibration curve showed that the prediction of the nomogram was in good agreement with the actual observation. The C-index of the nomogram for predicting survival was 0.73(95% CI, 0.67-0.78). The area under the ROC curve (AUC) for the nomogram to predict the survival for 1, 3, and 5-year was 0.726, 0.816, and 0.823, respectively. CONCLUSION: This proposed nomogram shows the potential to make a precise prediction regarding the prognosis of HBV-related HCC patients and may help to stratify patients for personalized therapy following partial hepatectomy.
BACKGROUND: Predicting the long-term prognosis of individuals who experienced sorafenib treatment following partial hepatectomy due to hepatitis B virus (HBV) related hepatocellular carcinoma (HCC) is difficult. This work aims to create an effective prognostic nomogram for HBV related HCC patients who are receiving sorafenib treatment as adjuvant therapy after surgery. METHODS: A total of 233 HBV-related HCC patients treated with or without sorafenib following partial hepatectomy at the Eastern Hepatobiliary Surgery Hospital from 2008 to 2013 were matched with propensity score matching analysis. The optimal cut-off point of the overall survival (OS) factor level was determined by x-tile. The selection of indicators was based on clinical findings. The Cox regression model with an interaction term was employed for evaluating the predictive value. Using a multivariate Cox proportional hazards model, a nomogram was subsequently formulated to analyze 111 patients treated with sorafenib. The nomogram's discriminative ability and predictive accuracy were determined using the concordance index (C-index), calibration, and ROC curve. RESULTS: The matched sorafenib cohort of 111 patients and control cohort of 118 patients were analyzed. Subgroup analysis revealed that low GPC3, pERK, pAKT, serum AFP levels, without MVI, under 50 years old, male, TNM stage I/II and BCLC stage 0/A were significantly associated with a better OS in patients subjected to sorafenib treatment compared to those without sorafenib treatment after surgery. Multivariate analysis of the sorafenib cohort revealed GPC3, pERK, pAKT, serum AST, and BCLC stage as independent factors for OS, and all were included in the nomogram. The survival probability based on the calibration curve showed that the prediction of the nomogram was in good agreement with the actual observation. The C-index of the nomogram for predicting survival was 0.73(95% CI, 0.67-0.78). The area under the ROC curve (AUC) for the nomogram to predict the survival for 1, 3, and 5-year was 0.726, 0.816, and 0.823, respectively. CONCLUSION: This proposed nomogram shows the potential to make a precise prediction regarding the prognosis of HBV-related HCC patients and may help to stratify patients for personalized therapy following partial hepatectomy.
Authors: Giorgio Ercolani; Gian Luca Grazi; Matteo Ravaioli; Massimo Del Gaudio; Andrea Gardini; Matteo Cescon; Giovanni Varotti; Francesco Cetta; Antonino Cavallari Journal: Ann Surg Date: 2003-04 Impact factor: 12.969
Authors: Scott M Wilhelm; Lila Adnane; Philippa Newell; Augusto Villanueva; Josep M Llovet; Mark Lynch Journal: Mol Cancer Ther Date: 2008-10 Impact factor: 6.261
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