Risk factors for liver cancer in chronic hepatitis B patients and construction of a nomogram prediction model

Yichen ZHU; Chunxia SHA; Chunsun FAN; Tiejun ZHANG

doi:10.12449/JCH241214

Volume 40 Issue 12

Dec. 2024

Turn off MathJax

Article Contents

Article Navigation > Journal of Clinical Hepatology > 2024 > 40(12): 2441-2449

PDF( 1065 KB)

Risk factors for liver cancer in chronic hepatitis B patients and construction of a nomogram prediction model

DOI: 10.12449/JCH241214

1.
Department of Epidemiology/Key Laboratory of Public Health Safety，Ministry of Education，School of Public Health，Fudan University，Shanghai 200032，China
2.
Department of Infection Management，Qidong Third People’s Hospital，Qidong，Jiangsu 226200，China
3.
Department of Scientific Research，Qidong People’s Hospital/Qidong Liver Cancer Institute/Affiliated Qidong Hospital of Nantong University，Qidong，Jiangsu 226200，China

Research funding:

National Key Research and Development Program of China (2021YFC2500405)

More Information

Corresponding author: ZHANG Tiejun， tjzhang@shmu.edu.cn （ORCID： 0000-0002-5187-7393）
Received Date: 2024-04-02
Accepted Date: 2024-05-23
Published Date: 2024-12-25

Abstract

Abstract

Objective To investigate the risk factors for liver cancer in patients with chronic hepatitis B （CHB） in the Qidong Chronic Hepatitis B cohort， and to construct a nomogram model for predicting the risk of liver cancer in CHB patients. Methods A structured questionnaire survey was conducted among the CHB patients， aged ≥18 years， who attended the outpatient service of Qidong Third People’s Hospital from January 1 to December 31， 2016. The onset of liver cancer was defined as the primary outcome， and the outcomes of the cohort were obtained from Qidong Cancer Registry. Baseline clinical features were compared；between the liver cancer group and the non-liver cancer group. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups. The Cox regression model was used to analyze the risk factors for liver cancer in CHB patients and calculate their hazard ratio （HR） and 95% confidence interval （CI）； the variables with statistical significance in the univariate Cox regression analysis were included in the LASSO regression analysis， and then the variables obtained were included in the multivariate Cox regression analysis to establish a predictive model. The nomogram was used to visualize the complex model. The receiver operating characteristic （ROC） curve， index of concordance （C-index）， and the calibration curve were used to assess the predictive efficacy of the model， and the decision curve was used to evaluate the clinical practicability of the nomogram. Results A total of 1 479 CHB patients were selected， among whom 58 patients with a confirmed diagnosis of liver cancer， 15 with missing data on testing indicators， and 164 with missing data on important information in the questionnaire were excluded， and finally 1 242 subjects were included in the study. Up to December 31， 2023， there were 67 new cases of liver cancer after a median follow-up time of 7.71 years， and the incidence density of liver cancer was 729.78/100，000 person-years. There were significant differences between the liver cancer group and the non-liver cancer group in age， sex， educational level， liver cirrhosis， duration of liver cirrhosis， history of diabetes mellitus， albumin， total bilirubin （TBil）， direct bilirubin， aspartate aminotransferase， aspartate aminotransferase， gamma-glutamyl transpeptidase （GGT）， and alkaline phosphatase （all P<0.05）. The multivariate Cox regression analysis showed that the increase in age （HR=1.07， 95%CI： 1.05‍ ‍—‍ ‍1.10， P<0.001）， a relatively high level of TBil （HR=1.98， 95%CI： 1.15‍ ‍—‍ ‍3.42， P=0.014）， a relatively high level of GGT （HR=2.41， 95%CI： 1.43‍ ‍—‍ ‍4.08， P=0.001）， and a long duration of liver cirrhosis （HR=1.09， 95%CI： 1.02‍ ‍—‍ ‍1.15， P=0.009） were independent risk factors for liver cancer in CHB patients. A nomogram prediction model was constructed based on the above four indicators， with an area under the ROC curve of 0.790， 0.845， and 0.829， respectively， in predicting the risk of liver cancer in CHB patients at 1， 3， and 5 years， and the bootstrap resampling method was used for internal validation and showed a C-index of 0. 778. The calibration curve showed that the prediction model had good stability， and the decision curve showed that it had certain clinical practicability. Conclusion The increase in age， relatively high levels of TBil and GGT， and a long duration of liver cirrhosis are independent risk factors for liver cancer in CHB patients， and the nomogram model constructed based on these factors has a good predictive value and can be used in clinical practice to help develop strategies for the long-term monitoring of liver cancer.
- Hepatitis B， Chronic,
- Liver Neoplasms,
- Risk Factors,
- Nomograms

FullText(HTML)

References(23)

References

[1]	TRÉPO C, CHAN HL, LOK A. Hepatitis B virus infection[J]. Lancet, 2014, 384( 9959): 2053- 2063. DOI: 10.1016/s0140-6736(14)60220-8.
[2]	Global Burden of Disease Liver Cancer Collaboration; AKINYEMIJU T, ABERA S, et al. The burden of primary liver cancer and underlying etiologies from 1990 to 2015 at the global, regional, and national level: Results from the global burden of disease study 2015[J]. JAMA Oncol, 2017, 3( 12): 1683- 1691. DOI: 10.1001/jamaoncol.2017.3055.
[3]	CHEN BY, XU HT, DING XY, et al. Serum B7-H2 and interleukin-6 levels in patients with hepatitis B virus-related primary liver cancer and their correlation with prognosis[J]. Trauma Crit Care Med, 2022, 10( 4): 292- 295, 299. DOI: 10.16048/j.issn.2095-5561.2022.04.13. 陈冰燕, 徐绘婷, 丁翔宇, 等. 乙型肝炎病毒相关原发性肝癌患者血清B7-H2、白细胞介素6水平及其与预后相关性研究[J]. 创伤与急危重病医学, 2022, 10( 4): 292- 295, 299. DOI: 10.16048/j.issn.2095-5561.2022.04.13.
[4]	ASRANI SK, DEVARBHAVI H, EATON J, et al. Burden of liver diseases in the world[J]. J Hepatol, 2019, 70( 1): 151- 171. DOI: 10.1016/j.jhep.2018.09.014.
[5]	SCHWEITZER A, HORN J, MIKOLAJCZYK RT, et al. Estimations of worldwide prevalence of chronic hepatitis B virus infection: A systematic review of data published between 1965 and 2013[J]. Lancet, 2015, 386( 10003): 1546- 1555. DOI: 10.1016/S0140-6736(15)61412-X.
[6]	LIU ZQ, MAO XH, JIANG YF, et al. Changing trends in the disease burden of primary liver cancer caused by specific etiologies in China[J]. Cancer Med, 2019, 8( 12): 5787- 5799. DOI: 10.1002/cam4.2477.
[7]	YUEN MF, TANAKA Y, FONG DY, et al. Independent risk factors and predictive score for the development of hepatocellular carcinoma in chronic hepatitis B[J]. J Hepatol, 2009, 50( 1): 80- 88. DOI: 10.1016/j.jhep.2008.07.023.
[8]	SHERMAN M. Hepatocellular carcinoma: Epidemiology, risk factors, and screening[J]. Semin Liver Dis, 2005, 25( 2): 143- 154. DOI: 10.1055/s-2005-871194.
[9]	CHEN CJ, YANG HI, SU J, et al. Risk of hepatocellular carcinoma across a biological gradient of serum hepatitis B virus DNA level[J]. JAMA, 2006, 295( 1): 65- 73. DOI: 10.1001/jama.295.1.65.
[10]	HE J, CHEN WQ, SHEN HB, et al. China guideline for liver cancer screening(2022, Beijing)[J]. J Clin Hepatol, 2022, 38( 8): 1739- 1758. DOI: 10.3969/j.issn.1001-5256.2022.08.007. 赫捷, 陈万青, 沈洪兵, 等. 中国人群肝癌筛查指南(2022, 北京)[J]. 临床肝胆病杂志, 2022, 38( 8): 1739- 1758. DOI: 10.3969/j.issn.1001-5256.2022.08.007.
[11]	LIANG F, SHA CX, FAN CS, et al. Qidong Chronic Hepatitis B Cohort: Participants enrollment and comparison of baseline characteristics by gender stratification[J]. Chin J Epidemiol, 2017, 38( 11): 1569- 1573. DOI: 10.3760/cma.j.issn.0254-6450.2017.11.026. 梁枫, 沙春霞, 樊春笋, 等. 启东慢性乙型肝炎临床队列: 建立及基线特征[J]. 中华流行病学杂志, 2017, 38( 11): 1569- 1573. DOI: 10.3760/cma.j.issn.0254-6450.2017.11.026.
[12]	KIM BK, AHN SH. Prediction model of hepatitis B virus-related hepatocellular carcinoma in patients receiving antiviral therapy[J]. J Formos Med Assoc, 2023, 122( 12): 1238- 1246. DOI: 10.1016/j.jfma.2023.05.029.
[13]	LEE HW, AHN SH. Prediction models of hepatocellular carcinoma development in chronic hepatitis B patients[J]. World J Gastroenterol, 2016, 22( 37): 8314- 8321. DOI: 10.3748/wjg.v22.i37.8314.
[14]	RAFFETTI E, FATTOVICH G, DONATO F. Incidence of hepatocellular carcinoma in untreated subjects with chronic hepatitis B: A systematic review and meta-analysis[J]. Liver Int, 2016, 36( 9): 1239- 1251. DOI: 10.1111/liv.13142.
[15]	WANG Y, WANG M, LI H, et al. A male-ABCD algorithm for hepatocellular carcinoma risk prediction in HBsAg carriers[J]. Chin J Cancer Res, 2021, 33( 3): 352- 363. DOI: 10.21147/j.issn.1000-9604.2021.03.07.
[16]	YANG HI, YUEN MF, CHAN HL, et al. Risk estimation for hepatocellular carcinoma in chronic hepatitis B(REACH-B): Development and validation of a predictive score[J]. Lancet Oncol, 2011, 12( 6): 568- 574. DOI: 10.1016/S1470-2045(11)70077-8.
[17]	FAN R, PAPATHEODORIDIS G, SUN J, et al. aMAP risk score predicts hepatocellular carcinoma development in patients with chronic hepatitis[J]. J Hepatol, 2020, 73( 6): 1368- 1378. DOI: 10.1016/j.jhep.2020.07.025.
[18]	YU JH, SUH YJ, JIN YJ, et al. Prediction model for hepatocellular carcinoma risk in treatment-naive chronic hepatitis B patients receiving entecavir/tenofovir[J]. Eur J Gastroenterol Hepatol, 2019, 31( 7): 865- 872. DOI: 10.1097/MEG.0000000000001357.
[19]	KIM JH, KIM YD, LEE M, et al. Modified PAGE-B score predicts the risk of hepatocellular carcinoma in Asians with chronic hepatitis B on antiviral therapy[J]. J Hepatol, 2018, 69( 5): 1066- 1073. DOI: 10.1016/j.jhep.2018.07.018.
[20]	YANG HI, SHERMAN M, SU J, et al. Nomograms for risk of hepatocellular carcinoma in patients with chronic hepatitis B virus infection[J]. J Clin Oncol, 2010, 28( 14): 2437- 2444. DOI: 10.1200/JCO.2009.27.4456.
[21]	WONG VW, CHAN SL, MO F, et al. Clinical scoring system to predict hepatocellular carcinoma in chronic hepatitis B carriers[J]. J Clin Oncol, 2010, 28( 10): 1660- 1665. DOI: 10.1200/JCO.2009.26.2675.
[22]	LIAW YF, SUNG JJY, CHOW WC, et al. Lamivudine for patients with chronic hepatitis B and advanced liver disease[J]. N Engl J Med, 2004, 351( 15): 1521- 1531. DOI: 10.1056/NEJMoa033364.
[23]	LIM YS, HAN S, HEO NY, et al. Mortality, liver transplantation, and hepatocellular carcinoma among patients with chronic hepatitis B treated with entecavir vs lamivudine[J]. Gastroenterology, 2014, 147( 1): 152- 161. DOI: 10.1053/j.gastro.2014.02.033.

Relative Articles

[1]	Aiping TIAN, Yongfeng YANG. Diagnosis of nonalcoholic fatty liver disease: The importance of pathology[J]. Journal of Clinical Hepatology, 2023, 39(3): 491-497. doi: 10.3969/j.issn.1001-5256.2023.03.002
[2]	Shengnan DU, Jingjing GAO, Tao WANG, Yuanye JIANG, Qin CAO. Value of circular RNA in the diagnosis and treatment of nonalcoholic fatty liver disease[J]. Journal of Clinical Hepatology, 2021, 37(11): 2684-2688. doi: 10.3969/j.issn.1001-5256.2021.11.043
[3]	Cong TONG, Yanian LI, Da GU, Xiang'an ZHAO, Xiaoxing XIANG. The association between obesity measurement indices and nonalcoholic fatty liver disease[J]. Journal of Clinical Hepatology, 2021, 37(10): 2465-2468. doi: 10.3969/j.issn.1001-5256.2021.10.044
[4]	Xiangqian HUANG, Xiaomeng YAN, Mingda ZHANG, Jing WU, Jianhong CHEN. Association between nonalcoholic fatty liver disease and colorectal neoplasms[J]. Journal of Clinical Hepatology, 2021, 37(12): 2947-2950. doi: 10.3969/j.issn.1001-5256.2021.12.045
[5]	Jiahe ZHAO, Xinyu MA, Jingya XU, Tingting DUAN, Chunlei ZHANG, Baolong LI. Research advances in related factors for autophagy in the regulation of nonalcoholic fatty liver disease[J]. Journal of Clinical Hepatology, 2021, 37(7): 1713-1717. doi: 10.3969/j.issn.1001-5256.2021.07.050
[6]	Gao Xin. New thoughts about renaming nonalcoholic fatty liver disease[J]. Journal of Clinical Hepatology, 2020, 36(6): 1201-1204. doi: 10.3969/j.issn.1001-5256.2020.06.001
[7]	A RuHan, Jia HaiYan, Ding YanHua, Niu JunQi. Research advances in nonalcoholic fatty liver disease in lean individuals[J]. Journal of Clinical Hepatology, 2020, 36(5): 1154-1159. doi: 10.3969/j.issn.1001-5256.2020.05.046
[8]	Li WenYi, Yuan ChengMin. Research advances in integrated traditional Chinese and Western medicine therapy for nonalcoholic fatty liver disease[J]. Journal of Clinical Hepatology, 2020, 36(4): 919-923. doi: 10.3969/j.issn.1001-5256.2020.04.047
[9]	YU Di, YANG XuYao, ZHAO JinHan, CHUAN LiXue, CHANG Jiang. Association between anxiety and nonalcoholic fatty liver disease[J]. Journal of Clinical Hepatology, 2020, 36(11): 2589-2592. doi: 10.3969/j.issn.1001-5256.2020.11.043
[10]	WANG Xin, HU YiYang, LIU Ping, FENG Qin. Association between hypertension and nonalcoholic fatty liver disease[J]. Journal of Clinical Hepatology, 2020, 36(11): 2584-2588. doi: 10.3969/j.issn.1001-5256.2020.11.042
[11]	Yang XuYao, Yu Di, Zhao JinHan, Chuan LiXue, Chang Jiang. Association between nonalcoholic fatty liver disease and depression[J]. Journal of Clinical Hepatology, 2020, 36(1): 201-204. doi: 10.3969/j.issn.1001-5256.2020.01.048
[12]	Ceng Jing, Fan JianGao. Clinical significance of renaming nonalcoholic fatty liver disease[J]. Journal of Clinical Hepatology, 2020, 36(6): 1205-1207. doi: 10.3969/j.issn.1001-5256.2020.06.002
[13]	Yao ChengZi, Feng Gong, Yu WenSi, Du Huan, Mi Man. Risk factors for the development and progression of nonalcoholic fatty liver disease[J]. Journal of Clinical Hepatology, 2020, 36(2): 433-436. doi: 10.3969/j.issn.1001-5256.2020.02.044
[14]	Jiang YuZi, Nie HongMing, Wang Rong. Research advances in the pathogenesis of nonalcoholic fatty liver disease[J]. Journal of Clinical Hepatology, 2019, 35(11): 2588-2591. doi: 10.3969/j.issn.1001-5256.2019.11.044
[15]	Gong Hang, Li LiangPing. Noninvasive diagnosis of progressive nonalcoholic fatty liver disease[J]. Journal of Clinical Hepatology, 2019, 35(2): 406-410. doi: 10.3969/j.issn.1001-5256.2019.02.038
[16]	Zhao LiQiong, Li LiangPing. Independent association between sarcopenia and nonalcoholic fatty liver disease[J]. Journal of Clinical Hepatology, 2019, 35(6): 1377-1379. doi: 10.3969/j.issn.1001-5256.2019.06.044
[17]	Chu PeiLing, Wang Qi, Guo XiaoQing, Liu JinChun. Association between chemokines and nonalcoholic fatty liver disease[J]. Journal of Clinical Hepatology, 2019, 35(7): 1626-1628. doi: 10.3969/j.issn.1001-5256.2019.07.044
[18]	Suo YuHong, Liu JinChun. Research advances in the treatment of nonalcoholic fatty liver disease[J]. Journal of Clinical Hepatology, 2018, 34(10): 2232-2236. doi: 10.3969/j.issn.1001-5256.2018.10.038
[19]	Xie Xiao, Lu LunGen. Potential therapeies for nonalcoholic fatty liver disease[J]. Journal of Clinical Hepatology, 2017, 33(12): 2439-2443. doi: 10.3969/j.issn.1001-5256.2017.12.042
[20]	Feng Gong, Niu ChunYan. Advances in the treatment of nonalcoholic fatty liver disease[J]. Journal of Clinical Hepatology, 2017, 33(12): 2433-2438. doi: 10.3969/j.issn.1001-5256.2017.12.041

Supplements(0)

Cited By

Cited by

Periodical cited type(4)

1.	杨宁宁，郑振，张然，武钰翔，王祺. 血清TSP2、APRI在2型糖尿病合并非酒精性脂肪性肝病诊断中的临床价值. 临床和实验医学杂志. 2025(04): 385-389 .
2.	宋传玉，李庆荣，李旭，孙富勇，贾磊. 枸杞多糖缓解非酒精性脂肪肝大鼠肝脏纤维化和肝脏炎症的研究表达水平. 宁夏医学杂志. 2025(02): 93-96+185 .
3.	贺艳，柯洪琴，李洪亮，朱建勇，赵利军，于慧斌. 美罗培南相关肝损伤的影响因素及其预测价值. 临床肝胆病杂志. 2025(03): 506-512 . 本站查看
4.	江小丽，李春汉，林丽雯，周俊铷，叶润杰，胡亦懿，谭力学. 基于瞬时弹性成像与血清学指标无创诊断肝纤维化模型的建立与评估. 现代消化及介入诊疗. 2024(08): 975-978 .

Other cited types(0)

Proportional views

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Figures(4) / Tables(4)

Get Citation

PDF

XML

Article Metrics

Article views (410) PDF downloads(76)