1. A preoperative risk score based on early recurrence for estimating outcomes after resection of hepatocellular carcinoma in the non-cirrhotic liver.
- Author
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Ruiz E, Honles J, Fernández R, Uribe K, Cerapio JP, Cancino K, Contreras-Mancilla J, Casavilca-Zambrano S, Berrospi F, Pineau P, and Bertani S
- Subjects
- Humans, Male, Female, Risk Assessment, Middle Aged, Aged, Risk Factors, Retrospective Studies, Time Factors, Treatment Outcome, Adult, Machine Learning, Liver Neoplasms surgery, Liver Neoplasms mortality, Liver Neoplasms pathology, Carcinoma, Hepatocellular surgery, Carcinoma, Hepatocellular mortality, Carcinoma, Hepatocellular pathology, Hepatectomy, Neoplasm Recurrence, Local
- Abstract
Background: Liver resection is the mainstay treatment option for patients with hepatocellular carcinoma in the non-cirrhotic liver (NCL-HCC), but almost half of these patients will experience a recurrence within five years of surgery. Therefore, we aimed to develop a rationale-based risk evaluation tool to assist surgeons in recurrence-related treatment planning for NCL-HCC., Methods: We analyzed single-center data from 263 patients who underwent liver resection for NCL-HCC. Using machine learning modeling, we first determined an optimal cut-off point to discriminate early versus late relapses based on time to recurrence. We then constructed a risk score based on preoperative variables to forecast outcomes according to recurrence-free survival., Results: We computed an optimal cut-off point for early recurrence at 12 months post-surgery. We identified macroscopic vascular invasion, multifocal tumor, and spontaneous tumor rupture as predictor variables of outcomes associated with early recurrence and integrated them into a scoring system. We thus stratified, with high concordance, three groups of patients on a graduated scale of recurrence-related survival., Conclusion: We constructed a preoperative risk score to estimate outcomes after liver resection in NCL-HCC patients. Hence, this score makes it possible to rationally stratify patients based on recurrence risk assessment for better treatment planning., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
- Published
- 2024
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