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Simple new clinical score to predict hepatocellular carcinoma after sustained viral response with direct-acting antivirals

The time point of the most precise predictor of hepatocellular carcinoma (HCC) development after viral eradication with direct-acting antiviral (DAA) therapy is unclear. In this study we developed a scoring system that can accurately predict the occurrence of HCC using data from the optimal time poi...

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Autores principales: Watanabe, Takao, Tokumoto, Yoshio, Joko, Kouji, Michitaka, Kojiro, Horiike, Norio, Tanaka, Yoshinori, Hiraoka, Atsushi, Tada, Fujimasa, Ochi, Hironori, Kisaka, Yoshiyasu, Nakanishi, Seiji, Yagi, Sen, Yamauchi, Kazuhiko, Higashino, Makoto, Hirooka, Kana, Morita, Makoto, Okazaki, Yuki, Yukimoto, Atsushi, Hirooka, Masashi, Abe, Masanori, Hiasa, Yoichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238506/
https://www.ncbi.nlm.nih.gov/pubmed/37268672
http://dx.doi.org/10.1038/s41598-023-36052-0
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author Watanabe, Takao
Tokumoto, Yoshio
Joko, Kouji
Michitaka, Kojiro
Horiike, Norio
Tanaka, Yoshinori
Hiraoka, Atsushi
Tada, Fujimasa
Ochi, Hironori
Kisaka, Yoshiyasu
Nakanishi, Seiji
Yagi, Sen
Yamauchi, Kazuhiko
Higashino, Makoto
Hirooka, Kana
Morita, Makoto
Okazaki, Yuki
Yukimoto, Atsushi
Hirooka, Masashi
Abe, Masanori
Hiasa, Yoichi
author_facet Watanabe, Takao
Tokumoto, Yoshio
Joko, Kouji
Michitaka, Kojiro
Horiike, Norio
Tanaka, Yoshinori
Hiraoka, Atsushi
Tada, Fujimasa
Ochi, Hironori
Kisaka, Yoshiyasu
Nakanishi, Seiji
Yagi, Sen
Yamauchi, Kazuhiko
Higashino, Makoto
Hirooka, Kana
Morita, Makoto
Okazaki, Yuki
Yukimoto, Atsushi
Hirooka, Masashi
Abe, Masanori
Hiasa, Yoichi
author_sort Watanabe, Takao
collection PubMed
description The time point of the most precise predictor of hepatocellular carcinoma (HCC) development after viral eradication with direct-acting antiviral (DAA) therapy is unclear. In this study we developed a scoring system that can accurately predict the occurrence of HCC using data from the optimal time point. A total of 1683 chronic hepatitis C patients without HCC who achieved sustained virological response (SVR) with DAA therapy were split into a training set (999 patients) and a validation set (684 patients). The most accurate predictive scoring system to estimate HCC incidence was developed using each of the factors at baseline, end of treatment, and SVR at 12 weeks (SVR12). Multivariate analysis identified diabetes, the fibrosis-4 (FIB-4) index, and the α-fetoprotein level as independent factors at SVR12 that contributed to HCC development. A prediction model was constructed with these factors that ranged from 0 to 6 points. No HCC was observed in the low-risk group. Five-year cumulative incidence rates of HCC were 1.9% in the intermediate-risk group and 15.3% in the high-risk group. The prediction model at SVR12 most accurately predicted HCC development compared with other time points. This simple scoring system combining factors at SVR12 can accurately evaluate HCC risk after DAA treatment.
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spelling pubmed-102385062023-06-04 Simple new clinical score to predict hepatocellular carcinoma after sustained viral response with direct-acting antivirals Watanabe, Takao Tokumoto, Yoshio Joko, Kouji Michitaka, Kojiro Horiike, Norio Tanaka, Yoshinori Hiraoka, Atsushi Tada, Fujimasa Ochi, Hironori Kisaka, Yoshiyasu Nakanishi, Seiji Yagi, Sen Yamauchi, Kazuhiko Higashino, Makoto Hirooka, Kana Morita, Makoto Okazaki, Yuki Yukimoto, Atsushi Hirooka, Masashi Abe, Masanori Hiasa, Yoichi Sci Rep Article The time point of the most precise predictor of hepatocellular carcinoma (HCC) development after viral eradication with direct-acting antiviral (DAA) therapy is unclear. In this study we developed a scoring system that can accurately predict the occurrence of HCC using data from the optimal time point. A total of 1683 chronic hepatitis C patients without HCC who achieved sustained virological response (SVR) with DAA therapy were split into a training set (999 patients) and a validation set (684 patients). The most accurate predictive scoring system to estimate HCC incidence was developed using each of the factors at baseline, end of treatment, and SVR at 12 weeks (SVR12). Multivariate analysis identified diabetes, the fibrosis-4 (FIB-4) index, and the α-fetoprotein level as independent factors at SVR12 that contributed to HCC development. A prediction model was constructed with these factors that ranged from 0 to 6 points. No HCC was observed in the low-risk group. Five-year cumulative incidence rates of HCC were 1.9% in the intermediate-risk group and 15.3% in the high-risk group. The prediction model at SVR12 most accurately predicted HCC development compared with other time points. This simple scoring system combining factors at SVR12 can accurately evaluate HCC risk after DAA treatment. Nature Publishing Group UK 2023-06-02 /pmc/articles/PMC10238506/ /pubmed/37268672 http://dx.doi.org/10.1038/s41598-023-36052-0 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
Watanabe, Takao
Tokumoto, Yoshio
Joko, Kouji
Michitaka, Kojiro
Horiike, Norio
Tanaka, Yoshinori
Hiraoka, Atsushi
Tada, Fujimasa
Ochi, Hironori
Kisaka, Yoshiyasu
Nakanishi, Seiji
Yagi, Sen
Yamauchi, Kazuhiko
Higashino, Makoto
Hirooka, Kana
Morita, Makoto
Okazaki, Yuki
Yukimoto, Atsushi
Hirooka, Masashi
Abe, Masanori
Hiasa, Yoichi
Simple new clinical score to predict hepatocellular carcinoma after sustained viral response with direct-acting antivirals
title Simple new clinical score to predict hepatocellular carcinoma after sustained viral response with direct-acting antivirals
title_full Simple new clinical score to predict hepatocellular carcinoma after sustained viral response with direct-acting antivirals
title_fullStr Simple new clinical score to predict hepatocellular carcinoma after sustained viral response with direct-acting antivirals
title_full_unstemmed Simple new clinical score to predict hepatocellular carcinoma after sustained viral response with direct-acting antivirals
title_short Simple new clinical score to predict hepatocellular carcinoma after sustained viral response with direct-acting antivirals
title_sort simple new clinical score to predict hepatocellular carcinoma after sustained viral response with direct-acting antivirals
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238506/
https://www.ncbi.nlm.nih.gov/pubmed/37268672
http://dx.doi.org/10.1038/s41598-023-36052-0
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