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Establishment and validation of a novel prognostic model for non-virus-related hepatocellular carcinoma.

Authors :
Jiang, Yu
Chen, Shulin
Wu, Yaxian
Qu, Yuanye
Jia, Lina
Xu, Qingxia
Dai, Shuqin
Xue, Ning
Source :
Cancer Cell International; 10/2/2022, Vol. 22 Issue 1, p1-11, 11p
Publication Year :
2022

Abstract

Objective: The incidence of non-virus-related hepatocellular carcinoma (NV-HCC) in hepatocellular carcinoma (HCC) is steadily increasing. The aim of this study was to establish a prognostic model to evaluate the overall survival (OS) of NV-HCC patients. Methods: Overall, 261 patients with NV-HCC were enrolled in this study. A prognostic model was developed by using LASSO-Cox regression analysis. The prognostic power was appraised by the concordance index (C-index), and the time-dependent receiver operating characteristic curve (TD-ROC). Kaplan–Meier (K–M) survival analysis was used to evaluate the predictive ability in the respective subgroups stratified by the prognostic model risk score. A nomogram for survival prediction was established by integrating the prognostic model, TNM stage, and treatment. Results: According to the LASSO-Cox regression results, the number of nodules, lymphocyte-to-monocyte ratio (LMR), prognostic nutritional index (PNI), alkaline phosphatase (ALP), aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratio (SLR) and C-reactive protein (CRP) were included for prognostic model construction. The C-index of the prognostic model was 0.759 (95% CI 0.723–0.797) in the development cohort and 0.796 (95% CI 0.737–0.855) in the validation cohort, and its predictive ability was better than TNM stage and treatment. The TD-ROC showed similar results. K–M survival analysis showed that NV-HCC patients with low risk scores had a better prognosis (P < 0.05). A nomogram based on the prognostic model, TNM stage, and treatment was constructed with sufficient discriminatory power with C-indexes of 0.78 and 0.85 in the development and validation cohort, respectively. Conclusion: For NV-HCC, this prognostic model could predict an OS benefit for patients, which may assist clinicians in designing individualized therapeutic strategies. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14752867
Volume :
22
Issue :
1
Database :
Complementary Index
Journal :
Cancer Cell International
Publication Type :
Academic Journal
Accession number :
159438909
Full Text :
https://doi.org/10.1186/s12935-022-02725-5