Construction and validation of a nomogram prediction model for the risk of liver dysfunction in liver cancer patients after transcatheter arterial chemoembolization
Objective To construct and validate a nomogram prediction model for the risk of liver dysfunction in liv-er cancer patients after transcatheter arterial chemoembolization(TACE).Method A total of 46 liver cancer patients with liver dysfunction after TACE(included in the liver dysfunction group)and 46 liver cancer patients without liver dys-function after TACE(included in the normal liver function group)were selected.The influencing factors of postoperative liver dysfunction in liver cancer patients after TACE were analyzed by multivariate Logistic regression model,and a no-mogram prediction model for liver dysfunction in liver cancer patients after TACE was constructed based on the influenc-ing factors.The receiver operating characteristic(ROC)curve was drawn,the area under the curve(AUC)was calculated,and the predictive value of nomogram prediction model for postoperative liver dysfunction in liver cancer patients after TACE was evaluated.The internal calibration curve was used to evaluate the accuracy of the nomogram prediction mod-el,and the decision curve was used to evaluate the external consistency of the nomogram prediction model.Result Mul-tivariate Logistic regression analysis showed that the type of massive liver cancer,concomitant cirrhosis,indocyanine green retention rate at 15 min(ICGR15)＞10％,Child-Pugh grade B,and albumin-bilirubin(ALBI)＞-1.39 were indepen-dent risk factors for postoperative liver dysfunction in liver cancer patients after TACE(P＜0.05).The nomogram predic-tion model has a moderate predictive value for postoperative liver dysfunction in liver cancer patients after TACE,the AUC was 0.755(95％CI:0.633-0.876).The calibration curve showed that the nomogram prediction model has high pre-dictive accuracy for postoperative liver dysfunction in liver cancer patients after TACE.The decision curve showed that the nomogram prediction model has better clinical net benefit in predicting postoperative liver dysfunction in liver cancer patients after TACE.Conclusion The type of massive liver cancer,concomitant cirrhosis,ICGR15＞10％,Child-Pugh grade B,and ALBI＞-1.39 are independent risk factors for postoperative liver dysfunction in liver cancer patients after TACE.The nomogram prediction model can guide clinical quantitative evaluation of the risk of postoperative liver dys-function in liver cancer patients after TACE,and has high clinical application value.
liver cancertranscatheter arterial chemoembolizationliver dysfunctionnomogram prediction model
万方数据
维普
