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Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma

BACKGROUND: Tumor recurrence after hepatectomy is high for hepatocellular carcinoma (HCC), and minimal residual disease (MRD) could be the underlying mechanism. A predictive model for recurrence and presence of MRD is needed. METHODS: Common inflammation-immune factors were reviewed and selected to...

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Autores principales: Xu, Xin, Huang, Ao, Guo, De-Zhen, Wang, Yu-Peng, Zhang, Shi-Yu, Yan, Jia-Yan, Wang, Xin-Yu, Cao, Ya, Fan, Jia, Zhou, Jian, Fu, Xiu-Tao, Shi, Ying-Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9213691/
https://www.ncbi.nlm.nih.gov/pubmed/35756674
http://dx.doi.org/10.3389/fonc.2022.893268
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author Xu, Xin
Huang, Ao
Guo, De-Zhen
Wang, Yu-Peng
Zhang, Shi-Yu
Yan, Jia-Yan
Wang, Xin-Yu
Cao, Ya
Fan, Jia
Zhou, Jian
Fu, Xiu-Tao
Shi, Ying-Hong
author_facet Xu, Xin
Huang, Ao
Guo, De-Zhen
Wang, Yu-Peng
Zhang, Shi-Yu
Yan, Jia-Yan
Wang, Xin-Yu
Cao, Ya
Fan, Jia
Zhou, Jian
Fu, Xiu-Tao
Shi, Ying-Hong
author_sort Xu, Xin
collection PubMed
description BACKGROUND: Tumor recurrence after hepatectomy is high for hepatocellular carcinoma (HCC), and minimal residual disease (MRD) could be the underlying mechanism. A predictive model for recurrence and presence of MRD is needed. METHODS: Common inflammation-immune factors were reviewed and selected to construct novel models. The model consisting of preoperative aspartate aminotransferase, C-reactive protein, and lymphocyte count, named ACLR, was selected and evaluated for clinical significance. RESULTS: Among the nine novel inflammation-immune models, ACLR showed the highest accuracy for overall survival (OS) and time to recurrence (TTR). At the optimal cutoff value of 80, patients with high ACLR (> 80) had larger tumor size, higher Edmondson’s grade, more vascular invasion, advanced tumor stage, and poorer survival than those with low ACLR (≤ 80) in the training cohort (5-year OS: 43.3% vs. 80.1%, P < 0.0001; 5-year TTR: 74.9% vs. 45.3%, P < 0.0001). Multivariate Cox analysis identified ACLR as an independent risk factor for OS [hazard ratio (HR) = 2.22, P < 0.001] and TTR (HR = 2.36, P < 0.001). Such clinical significance and prognostic value were verified in validation cohort. ACLR outperformed extant models, showing the highest area under receiver operating characteristics curve for 1-, 3-, and 5-year OS (0.737, 0.719, and 0.708) and 1-, 3-, and 5-year TTR (0.696, 0.650, and 0.629). High ACLR correlated with early recurrence (P < 0.001) and extremely early recurrence (P < 0.001). In patients with high ACLR, wide resection margin might confer survival benefit by decreasing recurrence (median TTR, 25.5 vs. 11.4 months; P = 0.037). CONCLUSIONS: The novel inflammation-immune model, ACLR, could effectively predict prognosis, and the presence of MRD before hepatectomy and might guide the decision on resection margin for patients with HCC.
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spelling pubmed-92136912022-06-23 Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma Xu, Xin Huang, Ao Guo, De-Zhen Wang, Yu-Peng Zhang, Shi-Yu Yan, Jia-Yan Wang, Xin-Yu Cao, Ya Fan, Jia Zhou, Jian Fu, Xiu-Tao Shi, Ying-Hong Front Oncol Oncology BACKGROUND: Tumor recurrence after hepatectomy is high for hepatocellular carcinoma (HCC), and minimal residual disease (MRD) could be the underlying mechanism. A predictive model for recurrence and presence of MRD is needed. METHODS: Common inflammation-immune factors were reviewed and selected to construct novel models. The model consisting of preoperative aspartate aminotransferase, C-reactive protein, and lymphocyte count, named ACLR, was selected and evaluated for clinical significance. RESULTS: Among the nine novel inflammation-immune models, ACLR showed the highest accuracy for overall survival (OS) and time to recurrence (TTR). At the optimal cutoff value of 80, patients with high ACLR (> 80) had larger tumor size, higher Edmondson’s grade, more vascular invasion, advanced tumor stage, and poorer survival than those with low ACLR (≤ 80) in the training cohort (5-year OS: 43.3% vs. 80.1%, P < 0.0001; 5-year TTR: 74.9% vs. 45.3%, P < 0.0001). Multivariate Cox analysis identified ACLR as an independent risk factor for OS [hazard ratio (HR) = 2.22, P < 0.001] and TTR (HR = 2.36, P < 0.001). Such clinical significance and prognostic value were verified in validation cohort. ACLR outperformed extant models, showing the highest area under receiver operating characteristics curve for 1-, 3-, and 5-year OS (0.737, 0.719, and 0.708) and 1-, 3-, and 5-year TTR (0.696, 0.650, and 0.629). High ACLR correlated with early recurrence (P < 0.001) and extremely early recurrence (P < 0.001). In patients with high ACLR, wide resection margin might confer survival benefit by decreasing recurrence (median TTR, 25.5 vs. 11.4 months; P = 0.037). CONCLUSIONS: The novel inflammation-immune model, ACLR, could effectively predict prognosis, and the presence of MRD before hepatectomy and might guide the decision on resection margin for patients with HCC. Frontiers Media S.A. 2022-06-08 /pmc/articles/PMC9213691/ /pubmed/35756674 http://dx.doi.org/10.3389/fonc.2022.893268 Text en Copyright © 2022 Xu, Huang, Guo, Wang, Zhang, Yan, Wang, Cao, Fan, Zhou, Fu and Shi https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Xu, Xin
Huang, Ao
Guo, De-Zhen
Wang, Yu-Peng
Zhang, Shi-Yu
Yan, Jia-Yan
Wang, Xin-Yu
Cao, Ya
Fan, Jia
Zhou, Jian
Fu, Xiu-Tao
Shi, Ying-Hong
Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma
title Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma
title_full Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma
title_fullStr Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma
title_full_unstemmed Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma
title_short Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma
title_sort integration of inflammation-immune factors to build prognostic model predictive of prognosis and minimal residual disease for hepatocellular carcinoma
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9213691/
https://www.ncbi.nlm.nih.gov/pubmed/35756674
http://dx.doi.org/10.3389/fonc.2022.893268
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