ArticleFrontiers in immunology2024
Machine learning-based model for predicting tumor recurrence after interventional therapy in HBV-related hepatocellular carcinoma patients with low preoperative platelet-albumin-bilirubin score.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Recurrence risk prediction model for hepatitis B virus-associated hepatocellular carcinoma patients: a systematic review and meta-analysis.Frontiers in oncology · 2026Pooled it
- Achieving "textbook outcome" after hepatectomy for hepatocellular carcinoma in the era of enhanced recovery: development and validation of a clinical nomogram.Frontiers in oncology · 2026Article
- NLR-PALBI Score and Its Grading: Predicting Overall Survival of Patients with Primary Liver Cancer Undergoing Transcatheter Arterial Chemoembolisation.Journal of hepatocellular carcinoma · 2026Article
- Construction and Validation of a Predictive Model for Post-TACE Recurrence Risk in Hepatocellular Carcinoma: A Retrospective Cohort Study.Journal of hepatocellular carcinoma · 2026Article
- The EZ-ALBI and PALBI scores contribute to the clinical application of ALBI in predicting postoperative recurrence of HCC.Scientific reports · 2025Article
- Applications of artificial intelligence in interventional oncology: An up-to-date review of the literature.Japanese journal of radiology · 2025Review
- Establishment and Validation of a Novel Nutritional-Immune-Inflammatory Score Model for Predicting Survival Prognosis in Hepatocellular Carcinoma Patients Treated with PD-1 Inhibitors.Journal of inflammation research · 2025Article
- Triglyceride-glucose index predicts postoperative overall survival in hepatocellular carcinoma: a retrospective cohort study.Discover oncology · 2024Article
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6 authors.
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Abstract
Introduction: This study aimed to develop a prognostic nomogram for predicting the recurrence-free survival (RFS) of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients with low preoperative platelet-albumin-bilirubin (PALBI) scores after transarterial chemoembolization (TACE) combined with local ablation treatment. Methods: We gathered clinical data from 632 HBV-related HCC patients who received the combination treatment at Beijing You'an Hospital, affiliated with Capital Medical University, from January 2014 to January 2020. The patients were divided into two groups based on their PALBI scores: low PALBI group (n=247) and high PALBI group (n=385). The low PALBI group was then divided into two cohorts: training cohort (n=172) and validation cohort (n=75). We utilized eXtreme Gradient Boosting (XGBoost), random survival forest (RSF), and multivariate Cox analysis to pinpoint the risk factors for RFS. Then, we developed a nomogram based on the screened factors and assessed its risk stratification capabilities and predictive performance. Results: The study finally identified age, aspartate aminotransferase (AST), and prothrombin time activity (PTA) as key predictors. The three variables were included to develop the nomogram for predicting the 1-, 3-, and 5-year RFS of HCC patients. We confirmed the nomogram's ability to effectively discern high and low risk patients, as evidenced by Kaplan-Meier curves. We further corroborated the excellent discrimination, consistency, and clinical utility of the nomogram through assessments using the C-index, area under the curve (AUC), calibration curve, and decision curve analysis (DCA). Conclusion: Our study successfully constructed a robust nomogram, effectively predicting 1-, 3-, and 5-year RFS for HBV-related HCC patients with low preoperative PALBI scores after TACE combined with local ablation therapy.
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