%0 Journal Article
%9 ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES
%A Ruiz, E.
%A Honles, J.
%A Fernández, R.
%A Uribe, K.
%A Cerapio, J. P.
%A Cancino, K.
%A Contreras-Mancilla, J.
%A Casavilca-Zambrano, S.
%A Berrospi, F.
%A Pineau, P.
%A Bertani, Stéphane
%T A preoperative risk score based on early recurrence for estimating outcomes after resection of hepatocellular carcinoma in the non-cirrhotic liver
%D 2024
%L fdi:010090691
%G ENG
%J HPB
%@ 1365-182X
%K PEROU
%M ISI:001237422500001
%N 5
%P 691-702
%R 10.1016/j.hpb.2024.02.010
%U https://www.documentation.ird.fr/hor/fdi:010090691
%> https://horizon.documentation.ird.fr/exl-doc/pleins_textes/2024-07/010090691.pdf
%V 26
%W Horizon (IRD)
%X 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 NCLHCC. 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 recurrencerelated 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.
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