Work

ASO Author Reflections: Enhancing Recurrence-Free Survival Prediction in Hepatocellular Carcinoma: A Time-Updated Model Incorporating Tumor Burden and AFP Dynamics

Year: 2025

Type: article

Abstract: Hepatocellular carcinoma (HCC) remains a global health challenge, with postoperative recurrence exceeding 40-50% within 2 years after curative-intent hepatectomy.1,2 Historically, prediction models have largely focused on static preoperative factors-most notably alpha-fetoprotein (AFP) and the tumor burden score (TBS)-to estimate recurrencefree survival (RFS).3,4 While offering valuable baseline insights, these predictors fail to capture changes in tumor biology that occur after resection.Serum AFP has long been monitored as a biomarker for HCC, reflecting active tumor growth or residual tumor cells.Prior models have not fully leveraged longitudinal AFP data, which may help inform evolving risk of recurrence.The current study investigated real-time RFS prediction by integrating time-updated AFP and tumor burden metrics.

Source: Annals of Surgical Oncology

DOI: 10.1245/s10434-025-17342-5

Authors: Miho Akabane, Timothy M. Pawlik

Institutions: The Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute, The Ohio State University Wexner Medical Center, The Ohio State University

Language: English

Topic: Hepatocellular Carcinoma Treatment and Prognosis

Subfield: Hepatology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $4,590