A sample model established by S-index predicting overall survival after curative resection of primary hepatocellular carcinoma
Authors Chen L, Cai BB, Zhou CJ, Hou XQ, Hu SP, Fang G, Chen WC, Li LH, Yang WJ
Received 6 November 2018
Accepted for publication 7 December 2018
Published 14 January 2019 Volume 2019:11 Pages 693—703
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Andrew Yee
Peer reviewer comments 2
Editor who approved publication: Professor Kenan Onel
Lei Chen,1 Bin-Bin Cai,1 Chao-Jun Zhou,1 Xiang-Qing Hou,2 Si-Pin Hu,1 Guan Fang,3 Wen-Chao Chen,1 Lin-Hui Li,1 Wen-Jun Yang1
1Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Zhejiang, Wenzhou, China; 2Department of Statistics, School of Public Health and Management, Wenzhou Medical University, Zhejiang, Wenzhou, China; 3Department of Colorectal Anus Surgery, The First Affiliated Hospital of Wenzhou Medical University, Zhejiang, Wenzhou, China
Purpose: Prognostic prediction after curative resection of primary hepatocellular carcinoma (PHCC) remains an arduous task. The S-index calculated from γ-glutamyl transpeptidase, albumin, and platelets is reported to predict the severity of liver fibrosis. We constructed a nomogram for predicting the survival probability of PHCC based on a new indicator, the S-index, combined with other routine clinical parameters.
Patients and methods: We selected 490 patients with PHCC postradical surgery at the First Affiliated Hospital of Wenzhou Medical University between January 2007 and January 2014. The subjects were randomly allocated into the training cohort and the validation cohort in the ratio 7:3 by the digital method. Important variables screened by univariate analysis were included in multivariate analysis to obtain independent risk factors for predicting the prognosis of PHCC. The construction of the nomogram was based on Cox proportional hazard regression models. The concordance index (C-index) was used in the nomogram for evaluating the model performance for prognosis. We drew time-dependent receiver operating characteristic curves to compare our model with other staging systems.
Results: The nomogram based on six independent risk factors after multivariate analyses had good predictive power after radical surgery of PHCC. In the training and validation groups, the C-index of the nomogram was highly consistent for evaluating survival from PHCC. Compared with the traditional scoring system, the areas under time-dependent receiver operating characteristic curves were 0.7382, 0.7293, and 0.7520 for 1-, 3-, and 5-year overall survival, respectively. In summary, the nomogram showed excellent results in terms of prognosis of PHCC.
Conclusion: Based on the S-index and the other clinical indicators, we developed a precise nomogram that predicts the survival probability of patients with PHCC after radical surgery. This tool can provide effective information for surgeons and patients.
Keywords: PHCC, radical resection, nomogram, prognosis
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