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经动脉化疗栓塞术后中晚期肝细胞癌患者 ALBI 评分轨迹:预后意义及影响因素分析
Authors Li J , Feng T, Cui C, Wang H, Su T, Jin L, Zhao X, Xiao W
Received 17 November 2024
Accepted for publication 23 April 2025
Published 5 May 2025 Volume 2025:12 Pages 865—878
DOI http://doi.org/10.2147/JHC.S503581
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr David Gerber
Jian Li,1 Tianyuyi Feng,2 Chi Cui,3 Haochen Wang,1 Tianhao Su,1 Long Jin,1,* Xiaohu Zhao,2,* Weizhong Xiao3,*
1The Department of Interventional Radiology of Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, People’s Republic of China; 2The Department of Radiology of the Fifth People’s Hospital of Shanghai, Fudan University, Shanghai, 200240, People’s Republic of China; 3Center of Vascular and Interventional Surgery, Department of General Surgery, The Third People’s Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University & The Second Affiliated Hospital of Chengdu, Chongqing Medical University, Chengdu, 610031, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Weizhong Xiao, Email weizhong_x@163.com
Objective: The long-term effects of transarterial chemoembolization (TACE) on liver function and their prognostic implications in hepatocellular carcinoma (HCC) have not been fully explored. The Albumin-Bilirubin (ALBI) score, an objective measure of liver function, is a validated prognostic tool in HCC. This study aims to characterize the longitudinal trajectories of ALBI-scores after TACE, evaluate their impact on clinical outcomes, and identify factors influencing these trajectories.
Materials and Methods: This retrospective study included patients with BCLC stage B/C HCC who underwent TACE, with baseline and at least two post-TACE ALBI-score measurements. Group-Based Trajectory Modeling (GBTM) was used to identify distinct ALBI-score trajectories. Clinical outcomes and patient characteristics were compared across trajectory groups. A CatBoost-based clinical prediction model was developed to identify factors influencing ALBI-score trajectories, with Shapley Additive Explanations (SHAP) values providing feature importance interpretation.
Results: Among 501 patients, three ALBI-score trajectories were identified: improve, stable, and decline. The improve group had better overall survival (OS) and progression-free survival (PFS) compared to the stable and decline groups. Multivariate analysis confirmed that ALBI-score trajectories were independent risk factors for OS. Subgroup analysis suggested that TACE plus systemic therapy reduced mortality risk in the stable and decline groups. The CatBoost model effectively distinguished distinct trajectory groups, with SHAP analysis highlighting ALBI-grade, Child-Pugh class, and tumor number as key predictors.
Conclusion: Post-TACE ALBI-score trajectories are closely linked to clinical outcomes, with improved liver function associated with better prognosis. Monitoring these trajectories could guide personalized treatment strategies for HCC patients undergoing TACE.
Keywords: hepatocellular carcinoma, transarterial chemoembolization, group-based trajectory modeling, machine learning, shapley additive explanations