Comparison of random forest and Cox regression models for predicting long-term survival after radical resection of HBV-associated hepatocellu-lar carcinoma
10.3969/j.issn.1009-9905.2025.05.004
- VernacularTitle:随机森林与Cox回归模型对HBV相关肝细胞癌根治性切除术后长期生存预测的对比
- Author:
Guang-zhou LI
1
;
Hong-lei WANG
1
;
Xi-quan CHEN
1
;
Yang HE
1
;
Yan-hao CHEN
1
;
Cui HU
1
;
Miao WANG
1
;
De-xiao ZHANG
1
Author Information
1. 南阳市第二人民医院 肝胆外科(河南 南阳 473000)
- Publication Type:Journal Article
- Keywords:
Hepatitis B;
Hepatocellular carcinoma;
Radical resection;
Survival;
Mortality;
Influence factor
- From:
Chinese Journal of Current Advances in General Surgery
2025;28(5):355-360
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the factors associated with long-term survival after radical resection of hepatitis B virus(HBV)-associated hepatocellular carcinoma(HCC),and to construct random forest and Cox regression models,to evaluate the two models.Methods:A total of 368 patients with HBV-infected HCC who underwent radical resection were selected retrospectively.These patients were categorized as having a good prognosis(n=266)or a poor prognosis(n=102)based on their survival and mortality status.Univariate and Cox regression analysis were used to identify fac-tors that predict poor prognosis in HCC patients after surgery,and Cox regression and random forest prediction models were constructed and evaluated.Results:There were significant differences in smoking history,Child-Pugh classifica-tion,cirrhosis,microvascular invasion,TNM staging,tumor capsule integrity,platelet-to-lymphocyte ratio(PLR),regular antiviral therapy,HBV-DNA load,alpha-fetoprotein(AFP),neutrophil-to-lymphocyte ratio(NLR),systemic immune in-flammatory index(SII),and albumin-to-globulin ratio(AGR)between the two groups(P<0.05);Cox regression showed that cirrhosis,microvascular invasion,regular antiviral treatment,HBV-DNA load,NLR,PLR,SII,and AGR were related factors that negatively affected the prognosis of patients with HBV-infected HCC after surgery(P<0.05),with an AUC of 0.870 for predicting prognosis;the importance ranking obtained by the random forest model was HBV-DNA load,cirrho-sis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII,with an AUC of 0.926 for predicting prog-nosis;the AUC predicted by the random forest model was greater than that predicted by the Cox regression model(Z=2.411,P=0.016).Conclusion:HBV-DNA load,cirrhosis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII are factors that affect the poor prognosis of patients with HBV-related HCC after surgery.The random for-est prediction model constructed based on these factors has high predictive value and is superior to the Cox regression prediction model.
