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Establishment, validation and evaluation of predictive model for early relapse after R0 resection in hepatocellular carcinoma patients with microvascular invasion

BACKGROUNDS: This is the first study to build and evaluate a predictive model for early relapse after R0 resection in hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI). METHODS: The consecutive HCC patients with MVI who underwent hepatectomy in Cancer Hospital of Chinese Acad...

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Autores principales: Zhang, Kai, Tao, Changcheng, Siqin, Tana, Wu, Jianxiong, Rong, Weiqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8261942/
https://www.ncbi.nlm.nih.gov/pubmed/34229698
http://dx.doi.org/10.1186/s12967-021-02940-0
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author Zhang, Kai
Tao, Changcheng
Siqin, Tana
Wu, Jianxiong
Rong, Weiqi
author_facet Zhang, Kai
Tao, Changcheng
Siqin, Tana
Wu, Jianxiong
Rong, Weiqi
author_sort Zhang, Kai
collection PubMed
description BACKGROUNDS: This is the first study to build and evaluate a predictive model for early relapse after R0 resection in hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI). METHODS: The consecutive HCC patients with MVI who underwent hepatectomy in Cancer Hospital of Chinese Academy of Medical Science from Jan 2014 to June 2019 were retrospectively enrolled and randomly allocated into a derivation (N = 286) and validation cohort (N = 120) in a ratio of 7:3. Cox regression and Logistic regression analyses were performed and a predictive model for postoperative early-relapse were developed. RESULTS: A total of 406 HCC patients with MVI were included in our work. Preoperative blood alpha-fetoprotein (AFP) level, hepatitis B e antigen (HBeAg) status, MVI classification, largest tumor diameter, the status of serosal invasion, number of tumors, and the status of satellite nodules were incorporated to construct a model. The concordance index (C-index) was 0.737 and 0.736 in the derivation and validation cohort, respectively. The calibration curves showed a good agreement between actual observation and nomogram prediction. The C-index of the nomogram was obviously higher than those of the two traditional HCC staging systems. CONCLUSION: We have developed and validated a prediction model for postoperative early-relapse in HCC patient with MVI after R0 resection. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-021-02940-0.
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spelling pubmed-82619422021-07-07 Establishment, validation and evaluation of predictive model for early relapse after R0 resection in hepatocellular carcinoma patients with microvascular invasion Zhang, Kai Tao, Changcheng Siqin, Tana Wu, Jianxiong Rong, Weiqi J Transl Med Research BACKGROUNDS: This is the first study to build and evaluate a predictive model for early relapse after R0 resection in hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI). METHODS: The consecutive HCC patients with MVI who underwent hepatectomy in Cancer Hospital of Chinese Academy of Medical Science from Jan 2014 to June 2019 were retrospectively enrolled and randomly allocated into a derivation (N = 286) and validation cohort (N = 120) in a ratio of 7:3. Cox regression and Logistic regression analyses were performed and a predictive model for postoperative early-relapse were developed. RESULTS: A total of 406 HCC patients with MVI were included in our work. Preoperative blood alpha-fetoprotein (AFP) level, hepatitis B e antigen (HBeAg) status, MVI classification, largest tumor diameter, the status of serosal invasion, number of tumors, and the status of satellite nodules were incorporated to construct a model. The concordance index (C-index) was 0.737 and 0.736 in the derivation and validation cohort, respectively. The calibration curves showed a good agreement between actual observation and nomogram prediction. The C-index of the nomogram was obviously higher than those of the two traditional HCC staging systems. CONCLUSION: We have developed and validated a prediction model for postoperative early-relapse in HCC patient with MVI after R0 resection. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-021-02940-0. BioMed Central 2021-07-06 /pmc/articles/PMC8261942/ /pubmed/34229698 http://dx.doi.org/10.1186/s12967-021-02940-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zhang, Kai
Tao, Changcheng
Siqin, Tana
Wu, Jianxiong
Rong, Weiqi
Establishment, validation and evaluation of predictive model for early relapse after R0 resection in hepatocellular carcinoma patients with microvascular invasion
title Establishment, validation and evaluation of predictive model for early relapse after R0 resection in hepatocellular carcinoma patients with microvascular invasion
title_full Establishment, validation and evaluation of predictive model for early relapse after R0 resection in hepatocellular carcinoma patients with microvascular invasion
title_fullStr Establishment, validation and evaluation of predictive model for early relapse after R0 resection in hepatocellular carcinoma patients with microvascular invasion
title_full_unstemmed Establishment, validation and evaluation of predictive model for early relapse after R0 resection in hepatocellular carcinoma patients with microvascular invasion
title_short Establishment, validation and evaluation of predictive model for early relapse after R0 resection in hepatocellular carcinoma patients with microvascular invasion
title_sort establishment, validation and evaluation of predictive model for early relapse after r0 resection in hepatocellular carcinoma patients with microvascular invasion
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8261942/
https://www.ncbi.nlm.nih.gov/pubmed/34229698
http://dx.doi.org/10.1186/s12967-021-02940-0
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