Very Early Recurrence After Liver Resection for Intrahepatic Cholangiocarcinoma: Considering Alternative Treatment Approaches

• Autor(a) principal: Tsilimigras, D
• Data de Publicação: 2020
• Outros Autores: Sahara, K, Wu, L, Moris, D, Bagante, F, Guglielmi, A, Aldrighetti, L, Weiss, M, Bauer, T, Alexandrescu, S, Poultsides, G, Maithel, S, Pinto Marques, H, Martel, G, Pulitano, C, Shen, F, Soubrane, O, Koerkamp, B, Moro, A, Sasaki, K, Aucejo, F, Zhang, XF, Matsuyama, R, Endo, I, Pawlik, T
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.17/3771
• topic: Aged; Bile Duct Neoplasms; Cholangiocarcinoma; Cohort Studies; Disease-Free Survival; Female; Humans; Logistic Models; Male; Middle Aged; Neoadjuvant Therapy; Neoplasm Recurrence, Local; Predictive Value of Tests; Risk Assessment; Survival Rate; Hepatectomy; HCC CIR

Importance: Although surgery offers the best chance of a potential cure for patients with localized, resectable intrahepatic cholangiocarcinoma (ICC), prognosis of patients remains dismal largely because of a high incidence of recurrence. Objective: To predict very early recurrence (VER) (ie, recurrence within 6 months after surgery) following resection for ICC in the pre- and postoperative setting. Design, setting, and participants: Patients who underwent curative-intent resection for ICC between May 1990 and July 2016 were identified from an international multi-institutional database. The study was conducted at The Ohio State University in collaboration with all other participating institutions. The data were analyzed in December 2019. Main outcomes and measures: Two logistic regression models were constructed to predict VER based on pre- and postoperative variables. The final models were used to develop an online calculator to predict VER and the tool was internally and externally validated. Results: Among 880 patients (median age, 59 years [interquartile range, 51-68 years]; 388 women [44.1%]; 428 [50.2%] white; 377 [44.3%] Asian; 27 [3.2%] black]), 196 (22.3%) developed VER. The 5-year overall survival among patients with and without VER was 8.9% vs 49.8%, respectively (P < .001). A preoperative model was able to stratify patients relative to the risk for VER: low risk (6-month recurrence-free survival [RFS], 87.7%), intermediate risk (6-month RFS, 72.3%), and high risk (6-month RFS, 49.5%) (log-rank P < .001). The postoperative model similarly identified discrete cohorts of patients based on probability for VER: low risk (6-month RFS, 90.0%), intermediate risk (6-month RFS, 73.1%), and high risk (6-month RFS, 48.5%) (log-rank, P < .001). The calibration and predictive accuracy of the pre- and postoperative models were good in the training (C index: preoperative, 0.710; postoperative, 0.722) as well as the internal (C index: preoperative, 0.715; postoperative, 0.728; bootstrapping resamples, n = 5000) and external (C index: postoperative, 0.672) validation data sets. Conclusion and relevance: An easy-to-use online calculator was developed to help clinicians predict the chance of VER after curative-intent resection for ICC. The tool performed well on internal and external validation. This tool may help clinicians in the preoperative selection of patients for neoadjuvant therapy as well as during the postoperative period to inform surveillance strategies.