Development and Validation of a Predictive Model for Liver Failure After Transarterial Chemoembolization Using
Xinru Wu1, Yihuan Wang1, Yiwei He1
1Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, China.
Rationale And Objectives:
Post-transarterial chemoembolization liver failure (PTLF) is a potentially fatal complication of transarterial chemoembolization (TACE). Accurate preoperative prediction of PTLF is crucial for improving patient outcomes. This study aimed to develop and validate a prediction model based on the functional liver imaging score (FLIS) to assess the risk of PTLF.
Materials And Methods:
A total of 156 patients underwent Gadoxetic acid-enhanced MRI within four weeks before TACE. Two radiologists, unaware of the clinical data, independently assessed FLIS on hepatobiliary phase images to quantitatively assess liver function. Univariate and multivariate logistic regression analyses identified independent predictors of PTLF. A nomogram was developed and subjected to internal validation through bootstrap resampling of 1000 samples. The model's performance was conducted through the area under the curve (AUC), Hosmer-Lemeshow test, calibration curves, and decision curve analysis (DCA). P< 0.05 was considered statistically significant.
Results:
PTLF occurred in 37.2% of patients (58/156). Significant differences were observed in factors such as portal vein thrombosis, albumin, aspartate transaminase, international normalized ratio (INR), model for end-stage liver disease scoring, albumin-bilirubin score, and FLIS. Multivariate analysis showed FLIS, portal vein thrombosis, and INR as independent predictors. The model achieved an AUC of 0.759, with 87.8% specificity and 56.9% sensitivity, and demonstrated good calibration (χ² = 7.101, P=0.526). Calibration curves and DCA confirmed its clinical utility.
Conclusion:
This FLIS-based prediction model performs well in predicting PTLF, potentially serving as a practical clinical tool.
