Background: Severe postoperative complications still occur following hepatectomy among patients with hepatocellular carcinoma (HCC). There is a need to identify high-risk patients for severe complications to enhance patient safety. We sought to evaluate the combined impact of pre- and postoperative albumin-bilirubin (ALBI) score and Fibrosis-4 (FIB-4) index trends to predict severe complications after HCC resection. Method: Patients with HCC undergoing curative-intent hepatectomy (2000–2023) were identified from an international, multi-institutional database. The cohort was divided into training (n = 439) and testing (n = 651) sets. ALBI score and FIB-4 index trends from preoperative to postoperative days 1, 3, and 5 were used for K-means clustering (K = 3). A logistic regression model was developed using the training set, and its performance was evaluated using the area under the receiver operating characteristic curve (AUC) in both cohorts. Results: Severe complications (Clavien-Dindo Grade ≥ IIIa) occurred in 118 patients (10.8 %); 43 (9.8 %) in training and 75 (11.5 %) in testing set (p = 0.42). K-means clustering identified three groups: Cluster1 (low), Cluster2 (intermediate), and Cluster3 (high), which was associated with a progressively increasing risk of complications (p < 0.01). On multivariable logistic regression, patients in ALBI Cluster1 had 76 % decreased odds (odds ratio[OR] 0.24, 95 % CI 0.07–0.83, p = 0.02) of postoperative complications relative to Cluster3 patients. Individuals categorized into FIB-4 Cluster1 had 85 % decreased odds (OR 0.15, 95 % CI 0.02–1.24, p = 0.07) versus patients in FIB-4 Cluster3. A new prediction model incorporating ALBI and FIB-4 index clusters achieved an AUC of 0.71, outperforming models based on preoperative data. A tool was made available at https://nm49jf-miho-akabane.shinyapps.io/HCC_ALBI/. Conclusion: A dynamic ALBI score and FIB-4 index trend tool improved risk stratification of patients undergoing resection of HCC relative to severe complications.
Dynamic ALBI score and FIB-4 index trends to predict complications after resection of hepatocellular carcinoma: A K-means clustering approach / Akabane, M.; Kawashima, J.; Altaf, A.; Woldesenbet, S.; Cauchy, F.; Aucejo, F.; Popescu, I.; Kitago, M.; Martel, G.; Ratti, F.; Aldrighetti, L.; Poultsides, G. A.; Imaoka, Y.; Ruzzenente, A.; Endo, I.; Gleisner, A.; Marques, H. P.; Lam, V.; Hugh, T.; Bhimani, N.; Shen, F.; Pawlik, T. M.. - In: EUROPEAN JOURNAL OF SURGICAL ONCOLOGY. - ISSN 0748-7983. - 51:6(2025). [10.1016/j.ejso.2025.109723]
Dynamic ALBI score and FIB-4 index trends to predict complications after resection of hepatocellular carcinoma: A K-means clustering approach
Ratti F.;Aldrighetti L.;
2025-01-01
Abstract
Background: Severe postoperative complications still occur following hepatectomy among patients with hepatocellular carcinoma (HCC). There is a need to identify high-risk patients for severe complications to enhance patient safety. We sought to evaluate the combined impact of pre- and postoperative albumin-bilirubin (ALBI) score and Fibrosis-4 (FIB-4) index trends to predict severe complications after HCC resection. Method: Patients with HCC undergoing curative-intent hepatectomy (2000–2023) were identified from an international, multi-institutional database. The cohort was divided into training (n = 439) and testing (n = 651) sets. ALBI score and FIB-4 index trends from preoperative to postoperative days 1, 3, and 5 were used for K-means clustering (K = 3). A logistic regression model was developed using the training set, and its performance was evaluated using the area under the receiver operating characteristic curve (AUC) in both cohorts. Results: Severe complications (Clavien-Dindo Grade ≥ IIIa) occurred in 118 patients (10.8 %); 43 (9.8 %) in training and 75 (11.5 %) in testing set (p = 0.42). K-means clustering identified three groups: Cluster1 (low), Cluster2 (intermediate), and Cluster3 (high), which was associated with a progressively increasing risk of complications (p < 0.01). On multivariable logistic regression, patients in ALBI Cluster1 had 76 % decreased odds (odds ratio[OR] 0.24, 95 % CI 0.07–0.83, p = 0.02) of postoperative complications relative to Cluster3 patients. Individuals categorized into FIB-4 Cluster1 had 85 % decreased odds (OR 0.15, 95 % CI 0.02–1.24, p = 0.07) versus patients in FIB-4 Cluster3. A new prediction model incorporating ALBI and FIB-4 index clusters achieved an AUC of 0.71, outperforming models based on preoperative data. A tool was made available at https://nm49jf-miho-akabane.shinyapps.io/HCC_ALBI/. Conclusion: A dynamic ALBI score and FIB-4 index trend tool improved risk stratification of patients undergoing resection of HCC relative to severe complications.| File | Dimensione | Formato | |
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