ALBI score combined with FIB-4 index to predict post-hepatectomy liver failure in patients with hepatocellular carcinoma

Author:

Tian Yi-Bo,Niu Hong,Xu Feng,Shang-Guan Peng-Wei,Song Wei-Wei

Abstract

AbstractPost-hepatectomy liver failure (PHLF) is a potentially life-threatening complication following liver resection. Hepatocellular carcinoma (HCC) often occurs in patients with chronic liver disease, which increases the risk of PHLF. This study aimed to investigate the ability of the combination of liver function and fibrosis markers (ALBI score and FIB-4 index) to predict PHLF in patients with HCC. Patients who underwent hepatectomy for HCC between August 2012 and September 2022 were considered for inclusion. Multivariable logistic regression analysis was used to identify factors associated with PHLF, and ALBI score and FIB-4 index were combined based on their regression coefficients. The performance of the combined ALBI-FIB4 score in predicting PHLF and postoperative mortality was compared with Child–Pugh score, MELD score, ALBI score, and FIB-4 index. A total of 215 patients were enrolled in this study. PHLF occurred in 35 patients (16.3%). The incidence of severe PHLF (grade B and grade C PHLF) was 9.3%. Postoperative 90‐d mortality was 2.8%. ALBI score, FIB-4 index, prothrombin time, and extent of liver resection were identified as independent factors for predicting PHLF. The AUC of the ALBI-FIB4 score in predicting PHLF was 0.783(95%CI: 0.694–0.872), higher than other models. The ALBI-FIB4 score could divide patients into two risk groups based on a cut-off value of − 1.82. High-risk patients had a high incidence of PHLF of 39.1%, while PHLF just occurred in 6.6% of low-risk patients. Similarly, the AUCs of the ALBI-FIB4 score in predicting severe PHLF and postoperative 90-d mortality were also higher than other models. Preoperative ALBI-FIB4 score showed good performance in predicting PHLF and postoperative mortality in patients undergoing hepatectomy for HCC, superior to the currently commonly used liver function and fibrosis scoring systems.

Publisher

Springer Science and Business Media LLC

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