A male-ABCD algorithm for hepatocellular carcinoma risk prediction in HBsAg carriers

Yuting Wang; Minjie Wang; He Li; Kun Chen; Hongmei Zeng; Xinyu Bi; Zheng Zhu; Yuchen Jiao; Yong Wang; Jian Zhu; Hui Zhao; Xiang Liu; Chunyun Dai; Chunsun Fan; Can Zhao; Deyin Guo; Hong Zhao; Jianguo Zhou; Dongmei Wang; Zhiyuan Wu; Xinming Zhao; Wei Cui; Xuehong Zhang; Jianqiang Cai; Wanqing Chen; Chunfeng Qu

doi:10.21147/j.issn.1000-9604.2021.03.07

A male-ABCD algorithm for hepatocellular carcinoma risk prediction in HBsAg carriers

Chin J Cancer Res. 2021 Jun 30;33(3):352-363. doi: 10.21147/j.issn.1000-9604.2021.03.07.

Authors

Yuting Wang¹, Minjie Wang², He Li³, Kun Chen¹, Hongmei Zeng⁴, Xinyu Bi⁵, Zheng Zhu⁶, Yuchen Jiao¹, Yong Wang⁷, Jian Zhu⁸, Hui Zhao⁹, Xiang Liu¹⁰, Chunyun Dai¹¹, Chunsun Fan⁸, Can Zhao¹², Deyin Guo¹³, Hong Zhao⁵, Jianguo Zhou⁵, Dongmei Wang¹, Zhiyuan Wu¹, Xinming Zhao⁶, Wei Cui², Xuehong Zhang^{14

15}, Jianqiang Cai⁵, Wanqing Chen³, Chunfeng Qu¹

Affiliations

¹ State Key Lab of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
² Department of Clinical Laboratory, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
³ Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
⁴ National Central Cancer Registry, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
⁵ Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
⁶ Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
⁷ Department of Ultrasonography, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
⁸ Qidong Liver Cancer Institute & Qidong People's Hospital, Qidong 226200, China.
⁹ Lingbi Center for Disease Control and Prevention, Suzhou 234200, China.
¹⁰ Mengcheng Center for Disease Control and Prevention, Bozhou 233500, China.
¹¹ Sheyang Center for Disease Control and Prevention, Yancheng 224300, China.
¹² Shenqiu County Center for Disease Control and Prevention, Zhoukou 411624, China.
¹³ Dancheng Center for Disease Control and Prevention, Zhoukou 477150, China.
¹⁴ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
¹⁵ Department of Nutrition, T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA.

PMID: 34321832
PMCID: PMC8286891
DOI: 10.21147/j.issn.1000-9604.2021.03.07

Abstract

Objective: Hepatocellular carcinoma (HCC) development among hepatitis B surface antigen (HBsAg) carriers shows gender disparity, influenced by underlying liver diseases that display variations in laboratory tests. We aimed to construct a risk-stratified HCC prediction model for HBsAg-positive male adults.

Methods: HBsAg-positive males of 35-69 years old (N=6,153) were included from a multi-center population-based liver cancer screening study. Randomly, three centers were set as training, the other three centers as validation. Within 2 years since initiation, we administrated at least two rounds of HCC screening using B-ultrasonography and α-fetoprotein (AFP). We used logistic regression models to determine potential risk factors, built and examined the operating characteristics of a point-based algorithm for HCC risk prediction.

Results: With 2 years of follow-up, 302 HCC cases were diagnosed. A male-ABCD algorithm was constructed including participant's age, blood levels of GGT (γ-glutamyl-transpeptidase), counts of platelets, white cells, concentration of DCP (des-γ-carboxy-prothrombin) and AFP, with scores ranging from 0 to 18.3. The area under receiver operating characteristic was 0.91 (0.90-0.93), larger than existing models. At 1.5 points of risk score, 26.10% of the participants in training cohort and 14.94% in validation cohort were recognized at low risk, with sensitivity of identifying HCC remained 100%. At 2.5 points, 46.51% of the participants in training cohort and 33.68% in validation cohort were recognized at low risk with 99.06% and 97.78% of sensitivity, respectively. At 4.5 points, only 20.86% of participants in training cohort and 23.73% in validation cohort were recognized at high risk, with positive prediction value of 22.85% and 12.35%, respectively.

Conclusions: Male-ABCD algorithm identified individual's risk for HCC occurrence within short term for their HCC precision surveillance.

Keywords: Hepatocellular carcinoma; asymptotic HBsAg carriers; laboratory tests; risk prediction model; screening.