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Personalized Antiviral Drug Selection in Patients With Chronic Hepatitis B Using a Machine Learning Model: A Multinational Study

Authors
 Moon Haeng Hur  ;  Min Kyung Park  ;  Terry Cheuk-Fung Yip  ;  Chien-Hung Chen  ;  Hyung-Chul Lee  ;  Won-Mook Choi  ;  Seung Up Kim  ;  Young-Suk Lim  ;  Soo Young Park  ;  Grace Lai-Hung Wong  ;  Dong Hyun Sinn  ;  Young-Joo Jin  ;  Sung Eun Kim  ;  Cheng-Yuan Peng  ;  Hyun Phil Shin  ;  Chi-Yi Chen  ;  Hwi Young Kim  ;  Han Ah Lee  ;  Yeon Seok Seo  ;  Dae Won Jun  ;  Eileen L Yoon  ;  Joo Hyun Sohn  ;  Sang Bong Ahn  ;  Jae-Jun Shim  ;  Soung Won Jeong  ;  Yong Kyun Cho  ;  Hyoung Su Kim  ;  Myoung-Jin Jang  ;  Yoon Jun Kim  ;  Jung-Hwan Yoon  ;  Jeong-Hoon Lee 
Citation
 AMERICAN JOURNAL OF GASTROENTEROLOGY, Vol.118(11) : 1963-1972, 2023-11 
Journal Title
AMERICAN JOURNAL OF GASTROENTEROLOGY
ISSN
 0002-9270 
Issue Date
2023-11
MeSH
Antiviral Agents / therapeutic use ; Artificial Intelligence ; Carcinoma, Hepatocellular* / complications ; Carcinoma, Hepatocellular* / epidemiology ; Carcinoma, Hepatocellular* / prevention & control ; Hepatitis B virus ; Hepatitis B, Chronic* / complications ; Hepatitis B, Chronic* / drug therapy ; Humans ; Liver Neoplasms* / complications ; Machine Learning ; Male ; Retrospective Studies ; Tenofovir / therapeutic use ; Treatment Outcome
Abstract
INTRODUCTION: Tenofovir disoproxil fumarate (TDF) is reportedly superior or at least comparable to entecavir (ETV) for the prevention of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B; however, it has distinct long-term renal and bone toxicities. This study aimed to develop and validate a machine learning model (designated as Prediction of Liver cancer using Artificial intelligence-driven model for Network-antiviral Selection for hepatitis B [PLAN-S]) to predict an individualized risk of HCC during ETV or TDF therapy.METHODS: This multinational study included 13,970 patients with chronic hepatitis B. The derivation (n = 6,790), Korean validation (n = 4,543), and Hong Kong-Taiwan validation cohorts (n = 2,637) were established. Patients were classified as the TDF-superior group when a PLAN-S-predicted HCC risk under ETV treatment is greater than under TDF treatment, and the others were defined as the TDF-nonsuperior group.RESULTS: The PLAN-S model was derived using 8 variables and generated a c-index between 0.67 and 0.78 for each cohort. The TDF-superior group included a higher proportion of male patients and patients with cirrhosis than the TDF-nonsuperior group. In the derivation, Korean validation, and Hong Kong-Taiwan validation cohorts, 65.3%, 63.5%, and 76.4% of patients were classified as the TDF-superior group, respectively. In the TDF-superior group of each cohort, TDF was associated with a significantly lower risk of HCC than ETV (hazard ratio = 0.60-0.73, all P < 0.05). In the TDF-nonsuperior group, however, there was no significant difference between the 2 drugs (hazard ratio = 1.16-1.29, all P > 0.1). [GRAPHICS] .DISCUSSION: Considering the individual HCC risk predicted by PLAN-S and the potential TDF-related toxicities, TDF and ETV treatment may be recommended for the TDF-superior and TDF-nonsuperior groups, respectively.
Full Text
https://journals.lww.com/ajg/fulltext/2023/11000/personalized_antiviral_drug_selection_in_patients.17.aspx
DOI
10.14309/ajg.0000000000002234
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
Yonsei Authors
Kim, Seung Up(김승업) ORCID logo https://orcid.org/0000-0002-9658-8050
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/197898
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