Risk factors for TACE resistance in hepatocellular carcinoma and the construction and validation of prediction model
Objective To analyze the risk factors of resistance to transcatheter arterial chemoembolization(TACE)in patients with hepatocellular carcinoma(HCC),to construct a prediction model,and to verify its prediction efficiency.Methods A total of 164 HCC patients who received at least 3 times of TACE were randomly divided into the training set(82 cases)and the test set(82 cases)at a ratio of 1∶1.According to the CCI definition of TACE resistance and expert con-sensus,TACE resistance was determined,and 49 cases were TACE effective and 33 cases were TACE resistant in the training set.In the validation set,58 cases were TACE effective and 24 cases were TACE resistant.The general data,lab-oratory examination data and imaging examination data of all subjects were collected.Multivariate Logistic regression model was used to analyze the risk factors of TACE resistance in the training set.The feature importance of predictor variables was screened by machine learning random forest classification and the prediction model nomogram was drawn.The area under the receiver operating characteristic(ROC)curve was used to verify the predictive efficacy of the prediction model.The Hosmer-Lemeshow goodness-of-fit test was used to evaluate the calibration ability of the prediction model.Results Mul-tivariate Logistic regression analysis showed that hepatitis B,high ALBI score,high level of alpha-fetoprotein(AFP),no tumor capsule,and enhancement pattern 3 and 4 were independent risk factors for TACE resistance in HCC(all P＜0.05).The feature importance of 5 independent risk factors of TACE resistance in the training set was evaluated by machine learning random forest,and we found that AFP(36.1%),enhancement pattern(30.4%),and ALBI score(26.5%)had higher feature importance,while non-tumor capsule(2.8%)and hepatitis B(4.1%)had lower feature importance,so they were excluded.AFP,enhancement pattern and ALBI score were used to construct a prediction model for TACE resistance of liver cancer and we drew a nomogram.ROC curve analysis showed that the area under the curve of the model in predicting TACE resistance of liver cancer was 0.899 in the training set and 0.753 in the test set.Hosmer-Lemeshow goodness-of-fit test showed that the model had good consistency in the training set and the test set(training set:χ2=11.829,P＞0.05;test set:χ2=7.927,P＞0.05).Conclusions Hepatitis B,high ALBI score,high level of AFP,absence of tumor capsule,enhancement patterns 3 and 4 were independent risk factors for TACE resistance in HCC.Based on ALBI score,AFP,and enhancement mode,a prediction model for TACE resistance of hepatocellular carcinoma was established,and the prediction efficiency of the model was good.
liver carcinomaresistance to transcatheter arterial chemoembolizationrisk factorsprediction model
国家科技期刊平台
NSTL
万方数据
维普
