Establishment and Evaluation of a Risk Prediction Model for Chronic Liver Failure Complicated by Primary Hepatocellular Carcinoma Before Intervention

Yuanzhen WANG; Hongyan WEI; Renhai TIAN; Yongzhen Chen; Danqing XU; Yingyuan ZHANG; Lixian CHANG; Chunyun LIU; Li LIU

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Yuanzhen WANG, Hongyan WEI, Renhai TIAN, Yongzhen Chen, Danqing XU, Yingyuan ZHANG, Lixian CHANG, Chunyun LIU, Li LIU. Establishment and Evaluation of a Risk Prediction Model for Chronic Liver Failure Complicated by Primary Hepatocellular Carcinoma Before Intervention[J]. Journal of Kunming Medical University.

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Establishment and Evaluation of a Risk Prediction Model for Chronic Liver Failure Complicated by Primary Hepatocellular Carcinoma Before Intervention

Yuanzhen WANG^{1, 2},
Hongyan WEI^{1, 2},
Renhai TIAN^{1, 2},
Yongzhen Chen^{1, 2},
Danqing XU¹,
Yingyuan ZHANG¹,
Lixian CHANG¹,
Chunyun LIU¹,
Li LIU^{1
,
,}

1.
Department of Liver Diseases and Immunology，The Third People’s Hospital of Kunming，Yunnan Province Communicable Disease Clinical Medical Center，Kunming Yunnan 650041
2.
School of Public Health，Dali University，Dali Yunnan 671000，China

Received Date: 2024-08-01
Available Online: 2025-02-20

Abstract

Abstract

Objective To analyze the influencing factors of chronic liver failure in patients with primary hepatic carcinoma （PHC） before intervention, and to establish and evaluate a nomogram risk prediction model. Methods A retrospective analysis was conducted by collecting general data and clinical test data within 24 hours of admission for PHC patients. Univariate analysis and Lasso regression were used for variable selection, followed by multivariate logistic regression analysis to identify independent influencing factors for CLF before PHC intervention, leading to the establishment of a nomogram risk prediction model. The model was evaluated using the Hosmer-Lemeshow test, receiver operating characteristic （ROC） curve, calibration curve, clinical decision curve, and clinical impact curve. Result A total of 353 cases of PHC patients were collected, including 153 cases in the liver failure group and 200 cases in the non-liver failure group, with a prevalence rate of 43.3%. Variables selected by Lasso regression included gastrointestinal bleeding, prothrombin time （PT）, albumin （ALB）, total bilirubin （TBIL）, and gamma glutamyl transferase （GGT）. Multivariate logistic regression analysis showed that gastrointestinal bleeding （OR = 13.549, 95%CI: 2.899～63.322, P = 0.001）, PT （OR = 1.599, 95%CI: 1.282～1.995, P < 0.001）, TBIL （OR = 1.016, 95%CI: 1.006～1.025, P = 0.002）, and GGT （OR = 1.002, 95%CI: 1.000～1.003, P = 0.028） were independent risk factors for chronic liver failure prior to PHC intervention, leading to the establishment of a nomogram risk prediction model. The Hosmer Lemeshow test showed that the model had a good fit （χ² = 6.152, P>0.05）; the area under ROC was 0.902 （0.869-0.934）, with a sensitivity of 80.4% and a specificity of 87.5%. The calibration curve indicated that the model predicts chronic liver failure prior to PHC intervention with good consistency. Clinical decision curve analysis and clinical impact curve analysis showed that the model has good clinical utility within a certain threshold range. Conclusion Gastrointestinal bleeding, PT≥16.05s, TBIL≥37.80 mmol/L, and GGT≥99.00 U/L are independent risk factors for the occurrence of chronic liver failure before PHC intervention. The established nomogram risk prediction model has certain clinical application value in predicting the risk of chronic liver failure before PHC intervention.
- Primary liver cancer,
- Chronic liver failure,
- Influencing factors,
- Prediction model

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