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Prognostication and risk factor stratification for survival of patients with hepatocellular carcinoma: a nationwide big data analysis
This study was conducted to identify risk factors affecting overall survival (OS) and provide prognostication for patients with hepatocellular carcinoma (HCC) using nationwide big data. Between January 2008 and December 2014, 10,573 adult patients with new HCC were registered in a nationwide databas...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10300189/ https://www.ncbi.nlm.nih.gov/pubmed/37369759 http://dx.doi.org/10.1038/s41598-023-37277-9 |
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author | Choi, Jin Woo Kang, Soohee Lee, Juhee Choi, Yunhee Kim, Hyo-Cheol Chung, Jin Wook |
author_facet | Choi, Jin Woo Kang, Soohee Lee, Juhee Choi, Yunhee Kim, Hyo-Cheol Chung, Jin Wook |
author_sort | Choi, Jin Woo |
collection | PubMed |
description | This study was conducted to identify risk factors affecting overall survival (OS) and provide prognostication for patients with hepatocellular carcinoma (HCC) using nationwide big data. Between January 2008 and December 2014, 10,573 adult patients with new HCC were registered in a nationwide database. Among them, 6830 patients without missing data were analyzed to construct a prognostication system. A validation cohort of 4580 patients was obtained from a tertiary hospital. All patients were assumed to have received the best treatment. A conditional inference tree analysis was performed to establish a prognostic system. The C-index and calibration plot for 5-year survival were estimated for validation. As a result, the tumor burden (TB) grade was the most significant factor in determining OS, and the cutoff was TB3 (TB1‒3 versus TB4). The patients were ultimately divided into 13 prognosis groups. The C-indexes were 0.714 and 0.737 (95% confidence interval, 0.733–0.742) in the nationwide (derivation) and hospital (validation) cohorts, respectively. In the calibration plot, the 5-year survival of the validation cohort largely matched the 45-degree line. In conclusion, the proposed prognostication system with a simple tree structure enabled the detailed stratification of patient prognosis and visualized the strata of risk factors affecting OS. |
format | Online Article Text |
id | pubmed-10300189 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103001892023-06-29 Prognostication and risk factor stratification for survival of patients with hepatocellular carcinoma: a nationwide big data analysis Choi, Jin Woo Kang, Soohee Lee, Juhee Choi, Yunhee Kim, Hyo-Cheol Chung, Jin Wook Sci Rep Article This study was conducted to identify risk factors affecting overall survival (OS) and provide prognostication for patients with hepatocellular carcinoma (HCC) using nationwide big data. Between January 2008 and December 2014, 10,573 adult patients with new HCC were registered in a nationwide database. Among them, 6830 patients without missing data were analyzed to construct a prognostication system. A validation cohort of 4580 patients was obtained from a tertiary hospital. All patients were assumed to have received the best treatment. A conditional inference tree analysis was performed to establish a prognostic system. The C-index and calibration plot for 5-year survival were estimated for validation. As a result, the tumor burden (TB) grade was the most significant factor in determining OS, and the cutoff was TB3 (TB1‒3 versus TB4). The patients were ultimately divided into 13 prognosis groups. The C-indexes were 0.714 and 0.737 (95% confidence interval, 0.733–0.742) in the nationwide (derivation) and hospital (validation) cohorts, respectively. In the calibration plot, the 5-year survival of the validation cohort largely matched the 45-degree line. In conclusion, the proposed prognostication system with a simple tree structure enabled the detailed stratification of patient prognosis and visualized the strata of risk factors affecting OS. Nature Publishing Group UK 2023-06-27 /pmc/articles/PMC10300189/ /pubmed/37369759 http://dx.doi.org/10.1038/s41598-023-37277-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/) . |
spellingShingle | Article Choi, Jin Woo Kang, Soohee Lee, Juhee Choi, Yunhee Kim, Hyo-Cheol Chung, Jin Wook Prognostication and risk factor stratification for survival of patients with hepatocellular carcinoma: a nationwide big data analysis |
title | Prognostication and risk factor stratification for survival of patients with hepatocellular carcinoma: a nationwide big data analysis |
title_full | Prognostication and risk factor stratification for survival of patients with hepatocellular carcinoma: a nationwide big data analysis |
title_fullStr | Prognostication and risk factor stratification for survival of patients with hepatocellular carcinoma: a nationwide big data analysis |
title_full_unstemmed | Prognostication and risk factor stratification for survival of patients with hepatocellular carcinoma: a nationwide big data analysis |
title_short | Prognostication and risk factor stratification for survival of patients with hepatocellular carcinoma: a nationwide big data analysis |
title_sort | prognostication and risk factor stratification for survival of patients with hepatocellular carcinoma: a nationwide big data analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10300189/ https://www.ncbi.nlm.nih.gov/pubmed/37369759 http://dx.doi.org/10.1038/s41598-023-37277-9 |
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