Title
A preoperative nomogram for predicting long-term survival after resection of large hepatocellular carcinoma (>10 cm)
Date Issued
01 February 2022
Access level
open access
Resource Type
journal article
Author(s)
RUIZ FIGUEROA, ELOY FRANCISCO
Pineau P.
Fernández R.
CASAVILCA ZAMBRANO, SANDRO ANGEL ANIBAL
CERAPIO ARROYO, JUAN PABLO
CHAVEZ PASSIURI, IVAN KLEVER
Roche B.
Université de Rennes
Université de Toulouse
Université de Toulouse
Publisher(s)
Elsevier
Abstract
Background: It has previously been demonstrated that a fraction of patients with hepatocellular carcinoma (HCC) > 10 cm can benefit from liver resection. However, there is still a lack of effective decision-making tools to inform intervention in these patients. Methods: We analysed a comprehensive set of clinical data from 234 patients who underwent liver resection for HCC >10 cm at the National Cancer Institute of Peru between 1990 and 2015, monitored their survival, and constructed a nomogram to predict the surgical outcome based on preoperative variables. Results: We identified cirrhosis, multifocality, macroscopic vascular invasion, and spontaneous tumour rupture as independent predictors of survival and integrated them into a nomogram model. The nomogram's ability to forecast survival at 1, 3, and 5 years was subsequently confirmed with high concordance using an internal validation. Through applying this nomogram, we stratified three groups of patients with different survival probabilities. Conclusion: We constructed a preoperative nomogram to predict long-term survival in patients with HCC >10 cm. This nomogram is useful in determining whether a patient with large HCC might truly benefit from liver resection, which is paramount in low- and middle-income countries where HCC is often diagnosed at advanced stages.
Start page
192
End page
201
Volume
24
Issue
2
Language
English
OCDE Knowledge area
Oncología
Scopus EID
2-s2.0-85109070570
PubMed ID
Source
HPB
ISSN of the container
1365182X
Source funding
H2020 Marie Skłodowska-Curie Actions
Sponsor(s)
This work was supported by the European Union's Horizon 2020 Framework Programme under the Marie Skłodowska-Curie Actions (Agreement N° 823935 ).
Sources of information:
Directorio de Producción Científica
Scopus