Ruiz E., Pineau P., Flores C., Fernández R., Cano L., Cerapio J.P., Casavilca-Zambrano S., Berrospi F., Chávez I., Roche Benjamin, Bertani Stéphane. (2022). A preoperative nomogram for predicting long-term survival after resection of large hepatocellular carcinoma (sup. 10 cm). HPB, 24 (2), 192-201. ISSN 1365-182X.
Titre du document
A preoperative nomogram for predicting long-term survival after resection of large hepatocellular carcinoma (sup. 10 cm)
Année de publication
Ruiz E., Pineau P., Flores C., Fernández R., Cano L., Cerapio J.P., Casavilca-Zambrano S., Berrospi F., Chávez I., Roche Benjamin, Bertani Stéphane
24 (2), 192-201 ISSN 1365-182X
Background: It has previously been demonstrated that a fraction of patients with hepatocellular carcinoma (HCC) sup. 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 sup.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 sup.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.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche 
Santé : généralités 
Fonds IRD [F B010082443]