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Updated: Jul 12, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Survival analysis and development of a prognostic nomogram for patients with hepatitis B virus-associated
Jianjun Wang1, Kexin Wang2, Chun Chen3
1Senior Department of Hepatology, Fifth Medical Center of Chinese PLA General Hospital, Beijing, 100039, China.
Background And Aims:
Hepatitis B virus (HBV) is a common cause of hepatocellular carcinoma (HCC) in China, and this study aimed to identify high-risk factors for overall survival and develop a nomogram prediction model.
Methods:
In the present retrospective cohort study, patients with HBV-associated HCC diagnosed from January 2009 to December 2018 were enrolled. Their clinical characteristics and time-to-event information were retrieved from electronic medical records. The zero time was the date of HCC diagnosis, and the endpoint was death or liver transplantation. Multivariable COX proportional hazard regression was used to screen independent risk factors for overall survival; then a nomogram model was developed to predict the survival probability of HCC patients.
Results:
A total of 1723 patients were enrolled, with 82.7 % male and a median age of 54.0 years. During a median follow-up time of 41.3 months, 672 cases (39.0 %) died. Age ≥60 years (HR = 1.209), Male (HR = 1.293), ALB <35 g/L (HR = 1.491), AST ≥80 U/L (HR = 1.818); AFP 20-400 ng/mL (HR = 2.284), AFP ≥400 ng/mL (HR = 2.746); LSM 9-22 kPa (HR = 2.266), LSM ≥22 kPa (HR = 4.326); BCLC stage B/C (HR = 4.079) and BCLC stage D (HR = 16.830) were the independent high-risk factors associated with HCC survival. A prognostic nomogram with a consistency index of 0.842 (95 % CI: 0.827-0.858) was developed. The calibration curve for long-term survival rate fitted well.
Conclusions:
This study identified independent risk factors affecting the survival of patients with HBV-associated HCC and constructed a predictive nomogram model, which can individually predict the overall survival and has good clinical application value.
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