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ISSN 2097-3497 (Online)
CN 22-1108/R
Volume 38 Issue 7
Jul.  2022
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Article Navigation >  Journal of Clinical Hepatology  > 2022  >  38(7): 1566-1571

Establishment of a nomogram model for predicting the survival of hepatitis B virus-related hepatocellular carcinoma

DOI: 10.3969/j.issn.1001-5256.2022.07.020
  • 1.

    Senior Department of Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing 100039, China

  • 2.

    Peking University 302 Clinical Medical School, Beijing 100039, China

  • 3.

    The Second Clinical Medical School of Southern Medical University, Guangzhou 510515, China

Research funding:

Medical Big Data and Artificial Intelligence Development Fund of Chinese PLA General Hospital (2019MBD-024);

Beijing Municipal Natural Science Foundation (7222173);

Science Technology and Innovation Committee of Shenzhen Municipality (KCXFZ202002011006448)

More Information
  • Corresponding author: LU Yinying, luyinying1973@163.com(ORCID: 0000-0002-7737-2334); JI Dong, jidg302@126.com(ORCID: 0000-0001-8214-462X)
  • Received Date: 2021-11-26
  • Accepted Date: 2022-01-24
  • Published Date: 2022-07-20
    Abstract
  •   Objective  To investigate the risk factors for death in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), and to establish a nomogram predictive model.  Methods  A retrospective analysis was performed for the clinical data of 700 patients who were diagnosed with HBV-related HCC for the first time in The Fifth Medical Center of Chinese PLA General Hospital from January 2010 to January 2020, and the starting point of follow-up was the date of HCC diagnosis, with death as the endpoint. According to the results of follow-up, the patients were divided into death group with 407 patients and survival group with 293 patients. The independent samples t-test or the Mann-Whitney U test was used for comparison of continuous data between groups, and the chi-square test was used for comparison of categorical data between groups. The Kaplan-Meier method was used to calculate survival rates, and the log-rank test was used for univariate analysis. The multivariate Cox proportional-hazards regression model was used to screen out independent risk factors and establish a nomogram model to predict 1-, 3-, and 5-year survival rates, and 10-fold cross validation was performed 200 times to evaluate the model.  Results  There were significant differences between the two groups in sex composition, albumin, total bilirubin, alanine aminotransferase, alpha-fetoprotein (AFP), cholinesterase (CHE), liver stiffness measurement (LSM), and Barcelona Clinic Liver Cancer (BCLC) stage (all P < 0.05). The multivariate analysis showed that male sex (hazard ratio [HR]=1.390, 95% confidence interval [CI]: 1.077-1.794, P < 0.05), CHE (2500-5000 U/L) (HR=1.996, 95%CI: 1.470-2.710, P < 0.05), CHE < 2500 U/L (HR=3.210, 95%CI: 2.188-4.709, P < 0.05), AFP≥400 ng/mL (HR=1.803, 95%CI: 1.412-2.303, P < 0.05), LSM ≥17.5 kPa (HR=1.719, 95%CI: 1.349-2.190, P < 0.05), BCLC stage B/C (HR=3.811, 95%CI: 2.994-4.852, P < 0.05), and BCLC stage D (HR=3.708, 95%CI: 2.520-5.455, P < 0.05) were independent risk factors for death. The nomogram model established based on the above factors had an index of concordance of 0.789 (95%CI: 0.769-0.809) with well-fitted calibration curves, and there was no significant difference between the predicted value of the model and the actual observed value.  Conclusion  The nomogram model established in this study can predict the 1-, 3-, and 5-year survival rates of HBV-related HCC patients and help to accurately assess the prognosis of patients.

     

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