Functional Liver Imaging Score to Predict Clinically Significant PHLF for Hepatocellular Carcinoma After Resection

功能性肝脏影像评分预测肝细胞癌切除术后临床显著性肝功能衰竭

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Abstract

PURPOSE: To develop a model based on Functional Liver Imaging Score (FLIS) to estimate the risk of clinically significant post-hepatectomy liver failure (PHLF) for hepatocellular carcinoma (HCC) after resection. PATIENTS AND METHODS: This retrospective study analyzed 885 patients with HCC who undergoing liver resection at our medical center between January 2017 and December 2021. Patients were randomly (7:3) assigned to development (n=620) or internal validation (n=265) cohorts. Univariable and multivariable logistic regression analyses were performed to identify independent risk factors for clinically significant PHLF, defined as grade B or C PHLF by the International Study Group of Liver Surgery. Predictive performance was assessed by the area under receiver operator characteristic curves (AUC). RESULTS: Clinically significant PHLF occurred in 7.7% of the development cohort and 7.2% of the internal validation cohort. Multivariate analysis identified FLIS, major resection and ALBI score as independent predictors of clinically significant PHLF, and a model combining these three variables predicted failure in the development cohort (AUC 0.746, 95% CI 0.673-0.820) and internal validation cohort (AUC 0.717, 95% CI 0.595-0.838). The same model also predicted mortality within 90 days after surgery in the development cohort (AUC 0.704, 95% CI 0.575-0.832) and internal validation cohort (AUC 0.717, 95% CI 0.586-0.848). In both cohorts, overall survival rate was significantly lower among patients whom the model placed at high risk of clinically significant PHLF than among those at low risk. CONCLUSION: The combination of FLIS and other easily acquired clinical data may reliably predict clinically significant PHLF and mortality in hepatocellular carcinoma.

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