AUTHOR=Yang Dashuai , Su Yang , Zhao Fangrui , Chen Chen , Zhao Kailiang , Xiong Xiangyun , Ding Youming 

TITLE=A Practical Nomogram and Risk Stratification System Predicting Cancer-Specific Survival for Hepatocellular Carcinoma Patients With Severe Liver Fibrosis

JOURNAL=Frontiers in Surgery

VOLUME=Volume 9 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/surgery/articles/10.3389/fsurg.2022.920589

DOI=10.3389/fsurg.2022.920589

ISSN=2296-875X

ABSTRACT=Objective: Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide. This study aimed to construct a novel practical nomogram and risk stratification system to predict cancer-specific survival (CSS) in HCC patients with severe liver fibrosis.
Methods: Data on 1878 HCC patients with severe liver fibrosis in the period 1975 to 2017 were extracted from the Surveillance, Epidemiology, and End Results database (SEER). Patients were block-randomized (1316 training cohort, 562 validation cohort) by setting random seed. Univariate and multivariate COX regression analysis were employed to select variables for the nomogram. Consistency index (C-index), area under time-dependent receiver operating characteristic curve (time-dependent AUC), and calibration curves were used to evaluate effective performance of the nomogram. Decision curve analysis (DCA), C-index, net reclassification index (NRI), and integrated discrimination improvement (IDI) were used to compare the nomogram with the AJCC tumor staging system. We also compared the risk stratification of the nomogram with American Joint Committee on Cancer (AJCC) staging system.
Results: Seven variables were selected to establish the nomogram. The C-index (training cohort: 0.781, 95%CI: 0.767-0.793; validation cohort: 0.793,95%CI=95%CI: 0.779-0.798) and the time-dependent AUCs (the training cohort: the values of 1-, 3-, 5- year were 0.845, 0.835, and 0.842; the validation cohort: the values of 1-, 3-, 5- year were 0.861, 0.870 and 0.876) showed satisfactory discrimination. The calibration plots also revealed that the nomogram was consistent with the actual observations. NRI (training cohort: 1-, 2-, 3-year CSS: 0.42, 0.61, 0.67; validation cohort: 1-, 2-, 3-year CSS: 0.26, 0.52, 0.72) and IDI (training cohort: 1-, 3-, 5-year CSS:0.16, 0.20, 0.22; validation cohort: 1-, 3-, 5-year CSS: 0.17, 0.26, 0.30) indicated that the established nomogram significantly outperformed AJCC staging system (P <0.001). Moreover, DCA also showed that the nomogram was more practical and had better recognition.
Conclusion: A nomogram for predicting CSS for HCC patients with severe liver fibrosis was established and validated, which provided a new system of risk stratification as a practical tool for individualized treatment and management.