J Hepatol. 2022;76(2):311-318.
An artificial intelligence model to predict hepatocellular carcinoma risk in Korean and Caucasian patients with chronic hepatitis B.
제1저자 김휘영, Lampertico P, 남준열, 이형철 · 교신저자 Papatheodoridis GV, 이정훈
소속 (33)
- Department of Internal Medicine, College of Medicine, Ewha Womans University, Seoul, Republic of Korea.
- Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Division of Gastroenterology and Hepatology, Milan, Italy; CRC "A. M. and A. Migliavacca" Center for Liver Disease, Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy.
- Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea.
- Department of Anesthesiology, Seoul National University College of Medicine, Seoul, Republic of Korea.
- Department of Internal Medicine and Yonsei Liver Center, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
- Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
- Department of Internal Medicine, Korea University Anam Hospital, Korea University College, Republic of Korea.
- Department of Internal Medicine, Korea University Anam Hospital, Korea University College, Republic of Korea; Department of Internal Medicine, Sanggye Paik Hospital, Inje University College of Medicine, Seoul, Republic of Korea.
- Department of Internal Medicine, School of Medicine, Kyungpook National University, Kyungpook National University Hospital, Daegu, Republic of Korea.
- Department of Internal Medicine, University of Ulsan College of Medicine, Asan Medical Centre, Seoul, Republic of Korea.
- Departments of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Republic of Korea.
- Department of Internal Medicine, Sanggye Paik Hospital, Inje University College of Medicine, Seoul, Republic of Korea; Department of Internal Medicine, Hanyang University Hospital, Hanyang University College of Medicine, Seoul, Republic of Korea.
- Department of Internal Medicine, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Republic of Korea.
- Department of Internal Medicine, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang-si, Republic of Korea.
- Department of Internal Medicine, Nowon Eulji Medical Center, Eulji University College of Medicine, Seoul, Republic of Korea.
- Department of Internal Medicine, Kyung Hee University School of Medicine, Seoul, Republic of Korea.
- Department of Internal Medicine, Soonchunhyang University College of Medicine, Soonchunhyang University Seoul Hospital, Seoul, Republic of Korea.
- Department of Internal Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Republic of Korea.
- Department of Internal Medicine, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri-si, Republic of Korea.
- Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
- Department of Internal Medicine, Hanyang University Hospital, Hanyang University College of Medicine, Seoul, Republic of Korea.
- Department of Medicine and Research Laboratory of Internal Medicine, National Expertise Center of Greece in Autoimmune Liver Diseases, General University Hospital of Larissa, Larissa, Greece.
- Department of Gastroenterology, Ankara University School of Medicine, Ankara, Turkey.
- Department of Hygiene, Epidemiology & Medical Statistics, Medical School of National and Kapodistrian University of Athens, Athens, Greece.
- Division of Hepatology, Department of Medicine II, Leipzig University Medical Center, Leipzig, Germany.
- Hospital General Universitario Vall Hebron and Ciberehd, Barcelona, Spain.
- Hospital U Puerta de Hierro, IDIPHIM CIBERehd, Madrid, Spain.
- 4th Department of Internal Medicine, Aristotle University of Thessaloniki Medical School, General Hospital of Thessaloniki "Hippokratio", Thessaloniki, Greece.
- 2nd Department of Internal Medicine, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens "Hippokratio", Athens, Greece.
- Liver Clinic, Toronto Western & General Hospital, University Health Network, Toronto, ON, Canada.
- Medical Research Collaboration Center, Seoul National University Hospital, Seoul, Republic of Korea.
- Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, General Hospital of Athens "Laiko", Athens, Greece. Electronic address: gepapath@med.uoa.gr.
- Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea. Electronic address: pindra@empal.com.
Abstract
BACKGROUND & AIMS Several models have recently been developed to predict risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). Our aims were to develop and validate an artificial intelligence-assisted prediction model of HCC risk.
METHODS Using a gradient-boosting machine (GBM) algorithm, a model was developed using 6,051 patients with CHB who received entecavir or tenofovir therapy from 4 hospitals in Korea. Two external validation cohorts were independently established: Korean (5,817 patients from 14 Korean centers) and Caucasian (1,640 from 11 Western centers) PAGE-B cohorts. The primary outcome was HCC development.
RESULTS In the derivation cohort and the 2 validation cohorts, cirrhosis was present in 26.9%-50.2% of patients at baseline. A model using 10 parameters at baseline was derived and showed good predictive performance (c-index 0.79). This model showed significantly better discrimination than previous models (PAGE-B, modified PAGE-B, REACH-B, and CU-HCC) in both the Korean (c-index 0.79 vs. 0.64-0.74; all p <0.001) and Caucasian validation cohorts (c-index 0.81 vs. 0.57-0.79; all p <0.05 except modified PAGE-B, p = 0.42). A calibration plot showed a satisfactory calibration function. When the patients were grouped into 4 risk groups, the minimal-risk group (11.2% of the Korean cohort and 8.8% of the Caucasian cohort) had a less than 0.5% risk of HCC during 8 years of follow-up.
CONCLUSIONS This GBM-based model provides the best predictive power for HCC risk in Korean and Caucasian patients with CHB treated with entecavir or tenofovir.
LAY SUMMARY Risk scores have been developed to predict the risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B. We developed and validated a new risk prediction model using machine learning algorithms in 13,508 antiviral-treated patients with chronic hepatitis B. Our new model, based on 10 common baseline characteristics, demonstrated superior performance in risk stratification compared with previous risk scores. This model also identified a group of patients at minimal risk of developing HCC, who could be indicated for less intensive HCC surveillance.
Copyright © 2021 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.
Keywords
HBVHCCantiviral treatmentchronic hepatitis Bdeep neural networkingliver cancer
Conflict of interest statement
Conflict of interest Hwi Young Kim: Nothing to declare; Pietro Lampertico: Speaking bureau/advisor for AbbVie, Eiger, Bristol-Myers Squibb, Gilead, GlaxoSmithKline, Merck/Merck Sharp & Dohme, MYR Pharma, Roche; Joon Yeul Nam: Nothing to declare; Hyung-Chul Lee: Nothing to declare; Seung Up Kim: Receiving grants from Yuhan Pharmaceuticals, and lecture fees from Bristol-Myers Squibb, Gilead Science and Yuhan Pharmaceuticals; Dong Hyun Sinn: Nothing to declare; Yeon Seok Seo: Nothing to declare; Han Ah Lee: Nothing to declare; Soo Young Park: Nothing to declare; Young-Suk Lim: Advisory board member of and receives research funding from Gilead Sciences; Eun Sun Jang: Nothing to declare; Eileen L. Yoon: Nothing to declare; Hyoung Su Kim: Nothing to declare; Sung Eun Kim: Nothing to declare; Sang Bong Ahn: Nothing to declare; Jae-Jun Shim: Nothing to declare; Soung Won Jeong: Nothing to declare; Yong Jin Jung: Nothing to declare; Joo Hyun Sohn: Nothing to declare; Yong Kyun Cho: Nothing to declare; Dae Won Jun: Nothing to declare; George N. Dalekos: Advisor/lecturer for AbbVie, Bayer, Bristol-Myers Squibb, Gilead, Janssen, Novartis, Roche; grant support from Bristol-Myers Squibb, Gilead, Roche; Ramazan Idilman: Nothing to declare; Vana Sypsa: Advisor/lecturer for AbbVie, Gilead, Janssen; research grants from AbbVie, Gilead; Thomas Berg: Advisor/consultant/lecturer for AbbVie, Alexion, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Gilead, GlaxoSmithKline, Janssen, Merck Sharp & Dohme/Merck, Novartis, Roche, and Vertex; Research support from AbbVie, Bristol-Myers Squibb, Gilead, Janssen, Merck Sharp & Dohme/Merck, Novartis and Roche; Maria Buti: Advisor/lecturer for AbbVie, Arbutus, Bristol-Myers Squibb, Gilead, Glaxo Smith-Kleine, Merck, Roche, Spring Bank; Jose Luis Calleja: Advisor/lecturer for AbbVie, Bristol-Myers Squibb, Gilead, Janssen, Merck; John Goulis: advisor/lecturer for Bristol-Myers Squibb, Gilead, GlaxoSmithKline, Merck Sharp & Dohme, Roche; research grant from Bristol-Myers Squibb; Spilios Manolakopoulos: Advisor/lecturer for AbbVie, Bristol-Myers Squibb, Gilead, GlaxoSmithKline, Merck Sharp & Dohme, Novartis, Roche; grants from Bristol-Myers Squibb, Gilead; Harry LA Janssen: Consultant for and grants from AbbVie, Arbutus, Bristol Myers Squibb, Enyo, Gilead Sciences, Janssen, Medimmune, Merck, Roche, Vir Biotechnology Inc., Viroclinics; Myoung-jin Jang: Nothing to declare; Yun Bin Lee: Research grant from Samjin Pharmaceuticals and Yuhan Pharmaceuticals; Yoon Jun Kim: Research grants from Bristol-Myers Squibb, Roche, JW Creagene, Bukwang Pharmaceuticals, Handok Pharmaceuticals, Hanmi Pharmaceuticals, Yuhan Pharmaceuticals and Pharmaking, and lecture fees from Bayer HealthCare Pharmaceuticals, Gilead Science, MSD Korea, Yuhan Pharmaceuticals, Samil Pharmaceuticals, CJ Pharmaceuticals, Bukwang Pharmaceuticals and Handok Pharmaceuticals; Jung-eHwan Yoon: Research grant from Bayer HealthCare Pharmaceuticals, Bukwang Pharmaceuticals and Daewoong Pharmaceuticals; Jeong-Hoon Lee: Lecture fees from GreenCross Cell, Daewoong Pharmaceuticals and Gilead Korea; George V. Papatheodoridis: Advisor/lecturer for AbbVie, Dicerna, Gilead, GlaxoSmithKline, Ipsen, Janssen, Merck Sharp & Dohme, Roche, Spring Bank; research grants AbbVie, Gilead. Please refer to the accompanying ICMJE disclosure forms for further details.
그 밖의 정보
- 출판 형태
- Journal Article, Research Support, Non-U.S. Gov't
- 저널
- Journal of hepatology · eISSN 1600-0641
- 전자 출판
- 2021-10-02
- MeSH
- Adult · Antiviral Agents / pharmacology / therapeutic use · Artificial Intelligence / standards / statistics & numerical data · Asian People / ethnology / statistics & numerical data · Carcinoma, Hepatocellular / etiology / physiopathology · Cohort Studies · Computer Simulation / standards / statistics & numerical data · Female · Follow-Up Studies · Guanine / analogs & derivatives / pharmacology / therapeutic use · Hepatitis B, Chronic / complications / physiopathology · Humans · Liver Neoplasms / complications / physiopathology · Male · Middle Aged · Republic of Korea / ethnology · Tenofovir / pharmacology / therapeutic use · White People / ethnology / statistics & numerical data
- Substances
- Antiviral Agents · entecavir · Guanine · Tenofovir