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The concept of therapeutic hierarchy for patients with hepatocellular carcinoma: A multicenter cohort study
Author(s) -
Vitale Alessandro,
Farinati Fabio,
Pawlik Timothy M.,
Frigo Anna Chiara,
Giannini Edoardo G.,
Napoli Lucia,
Ciccarese Francesco,
Rapaccini Gian Ludovico,
Di Marco Maria,
Caturelli Eugenio,
Zoli Marco,
Borzio Franco,
Sacco Rodolfo,
Cabibbo Giuseppe,
Virdone Roberto,
Marra Fabio,
Felder Martina,
Morisco Filomena,
Benvegnù Luisa,
Gasbarrini Antonio,
SvegliatiBaroni Gianluca,
Foschi Francesco Giuseppe,
Missale Gabriele,
Masotto Alberto,
Nardone Gerardo,
Colecchia Antonio,
Bernardi Mauro,
Trevisani Franco,
Cillo Umberto
Publication year - 2019
Publication title -
liver international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.873
H-Index - 110
eISSN - 1478-3231
pISSN - 1478-3223
DOI - 10.1111/liv.14154
Subject(s) - hepatocellular carcinoma , sorafenib , medicine , hazard ratio , liver transplantation , confidence interval , multivariate analysis , oncology , liver cancer , cohort , gastroenterology , transplantation
Background The Italian Liver Cancer (ITA.LI.CA) prognostic system for patients with hepatocellular carcinoma (HCC) has recently been proposed and validated. We sought to explore the relationship among the ITA.LI.CA prognostic variables (ie tumour stage, functional score based on performance status and Child‐Pugh score, and alpha‐fetoprotein), treatment selection and survival outcome in HCC patients. Patients and Methods We analysed 4,867 consecutive HCC patients undergoing six main treatment strategies (liver transplantation, LT; liver resection, LR; ablation, ABL; intra‐arterial therapy, IAT; Sorafenib, SOR; and best supportive care, BSC) and enrolled during 2002‐2015 in a multicenter Italian database. In order to control pretreatment imbalances in observed variables, a machine learning methodology was used and inverse probability of treatment weights (IPTW) was calculated. An IPTW‐adjusted multivariate survival model that included ITA.LI.CA prognostic variables, treatment period and treatment strategy was then developed. The survival benefit of HCC treatments was described as a hazard ratio (95% confidence interval), using BSC as a reference value and as predicted median survival. Results After the IPTW, the six treatment groups became well balanced for most baseline characteristics. In the IPTW‐adjusted multivariate survival model, treatment strategy was found to be the strongest survival predictor, irrespective of ITA.LI.CA prognostic variables and treatment period. The survival benefit of different therapies over BSC was: LT = 0.19 (0.18‐0.20); RES = 0.40 (0.37‐0.42); ABL 0.42 (0.40‐0.44); IAT = 0.58 (0.55‐0.61); SOR = 0.92 (0.87‐0.97). This multivariate model was then used to predict median survival for each therapy within each ITA.LI.CA stage. Conclusion The concept of therapeutic hierarchy was established within each ITA.LI.CA stage.