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Prediction of survival and analysis of prognostic factors for hepatocellular carcinoma: a 20-year of imaging diagnosis in Upper Northern Thailand
BACKGROUND: To evaluate survival rates of hepatocellular carcinoma (HCC), the Chiang Mai Cancer Registry provided characteristics data of 6276 HCC patients diagnosed between 1998-2020 based on evolution of imaging diagnosis. Evolution can be separated into four cohorts, namely, cohort 1 (1990-2005)...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10625219/ https://www.ncbi.nlm.nih.gov/pubmed/37923991 http://dx.doi.org/10.1186/s12885-023-11429-6 |
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author | Nakharutai, Nawapon Chitapanarux, Imjai Traisathit, Patrinee Srikummoon, Pimwarat Pojchamarnwiputh, Suwalee Inmutto, Nakarin Na Chiangmai, Wittanee |
author_facet | Nakharutai, Nawapon Chitapanarux, Imjai Traisathit, Patrinee Srikummoon, Pimwarat Pojchamarnwiputh, Suwalee Inmutto, Nakarin Na Chiangmai, Wittanee |
author_sort | Nakharutai, Nawapon |
collection | PubMed |
description | BACKGROUND: To evaluate survival rates of hepatocellular carcinoma (HCC), the Chiang Mai Cancer Registry provided characteristics data of 6276 HCC patients diagnosed between 1998-2020 based on evolution of imaging diagnosis. Evolution can be separated into four cohorts, namely, cohort 1 (1990-2005) when we had ultrasound (US) and single-phase computed tomography (CT), cohort 2 (2006-2009) when one multi-phase CT and one magnetic resonance imaging (MRI) were added, cohort 3 (2010-2015) when MRI with LI-RADS was added, and finally, cohort 4 (2016-2020) when two upgraded MRIs with LI-RADS were added. METHODS: Cox proportional hazard models were used to determine the relation between death and risk factors including methods of imagining diagnosis, gender, age of diagnosis, tumor stages, history of smoking and alcohol-use, while Kaplan-Meier curves were used to calculate survival rates. RESULTS: The median age of diagnosis was 57.0 years (IQR: 50.0-65.0) and the median survival time was 5.8 months (IQR: 1.9-26.8) during the follow-up period. In the univariable analysis, all factors were all associated with a higher risk of death in HCC patients except age of diagnosis. In a multivariable analysis, elderly age at diagnosis, regional and metastatic stages and advanced methods of imagining diagnosis during cohorts 2 and 3 were independently associated with the risk of death in HCC patients. The survival rate of patients diagnosed during cohort 4 was significantly higher than the other cohorts. CONCLUSION: As a significantly increasing survival rate of HCC patients in cohort 4, advanced methods of diagnostic imaging can be a part of the recommendation to diagnose HCC. |
format | Online Article Text |
id | pubmed-10625219 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106252192023-11-05 Prediction of survival and analysis of prognostic factors for hepatocellular carcinoma: a 20-year of imaging diagnosis in Upper Northern Thailand Nakharutai, Nawapon Chitapanarux, Imjai Traisathit, Patrinee Srikummoon, Pimwarat Pojchamarnwiputh, Suwalee Inmutto, Nakarin Na Chiangmai, Wittanee BMC Cancer Research BACKGROUND: To evaluate survival rates of hepatocellular carcinoma (HCC), the Chiang Mai Cancer Registry provided characteristics data of 6276 HCC patients diagnosed between 1998-2020 based on evolution of imaging diagnosis. Evolution can be separated into four cohorts, namely, cohort 1 (1990-2005) when we had ultrasound (US) and single-phase computed tomography (CT), cohort 2 (2006-2009) when one multi-phase CT and one magnetic resonance imaging (MRI) were added, cohort 3 (2010-2015) when MRI with LI-RADS was added, and finally, cohort 4 (2016-2020) when two upgraded MRIs with LI-RADS were added. METHODS: Cox proportional hazard models were used to determine the relation between death and risk factors including methods of imagining diagnosis, gender, age of diagnosis, tumor stages, history of smoking and alcohol-use, while Kaplan-Meier curves were used to calculate survival rates. RESULTS: The median age of diagnosis was 57.0 years (IQR: 50.0-65.0) and the median survival time was 5.8 months (IQR: 1.9-26.8) during the follow-up period. In the univariable analysis, all factors were all associated with a higher risk of death in HCC patients except age of diagnosis. In a multivariable analysis, elderly age at diagnosis, regional and metastatic stages and advanced methods of imagining diagnosis during cohorts 2 and 3 were independently associated with the risk of death in HCC patients. The survival rate of patients diagnosed during cohort 4 was significantly higher than the other cohorts. CONCLUSION: As a significantly increasing survival rate of HCC patients in cohort 4, advanced methods of diagnostic imaging can be a part of the recommendation to diagnose HCC. BioMed Central 2023-11-04 /pmc/articles/PMC10625219/ /pubmed/37923991 http://dx.doi.org/10.1186/s12885-023-11429-6 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/) . 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 Nakharutai, Nawapon Chitapanarux, Imjai Traisathit, Patrinee Srikummoon, Pimwarat Pojchamarnwiputh, Suwalee Inmutto, Nakarin Na Chiangmai, Wittanee Prediction of survival and analysis of prognostic factors for hepatocellular carcinoma: a 20-year of imaging diagnosis in Upper Northern Thailand |
title | Prediction of survival and analysis of prognostic factors for hepatocellular carcinoma: a 20-year of imaging diagnosis in Upper Northern Thailand |
title_full | Prediction of survival and analysis of prognostic factors for hepatocellular carcinoma: a 20-year of imaging diagnosis in Upper Northern Thailand |
title_fullStr | Prediction of survival and analysis of prognostic factors for hepatocellular carcinoma: a 20-year of imaging diagnosis in Upper Northern Thailand |
title_full_unstemmed | Prediction of survival and analysis of prognostic factors for hepatocellular carcinoma: a 20-year of imaging diagnosis in Upper Northern Thailand |
title_short | Prediction of survival and analysis of prognostic factors for hepatocellular carcinoma: a 20-year of imaging diagnosis in Upper Northern Thailand |
title_sort | prediction of survival and analysis of prognostic factors for hepatocellular carcinoma: a 20-year of imaging diagnosis in upper northern thailand |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10625219/ https://www.ncbi.nlm.nih.gov/pubmed/37923991 http://dx.doi.org/10.1186/s12885-023-11429-6 |
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