Identification of lenvatinib prognostic index via recursive partitioning analysis in advanced hepatocellular carcinoma.

Background: After the advent of new treatment options for advanced hepatocellular carcinoma (HCC), the identification of prognostic factors is crucial for the selection of the most appropriate therapy for each patient.
Patients and Methods: With the aim to fill this gap, we applied recursive partitioning analysis (RPA) to a cohort of 404 patients treated with lenvatinib.
Results: The application of RPA resulted in a classification based on five variables that originated a new prognostic score, the lenvatinib prognostic index (LEP) index, identifying three groups: low risk [patients with prognostic nutritional index (PNI) >43.3 and previous trans-arterial chemoembolization (TACE)]; medium risk [patients with PNI >43.3 but without previous TACE and patients with PNI <43.3, albumin-bilirubin (ALBI) grade 1 and Barcelona Clinic Liver Cancer stage B (BCLC-B)]; high risk [patients with PNI <43.3 and ALBI grade 2 and patients with PNI <43.3, albumin-bilirubin (ALBI) grade 1 and Barcelona Clinic Liver Cancer stage C (BCLC-C)]. Median overall survival was 29.8 months [95% confidence interval (CI) 22.8-29.8 months] in low risk patients (n = 128), 17.0 months (95% CI 15.0-24.0 months) in medium risk (n = 162) and 8.9 months (95% CI 8.0-10.7 months) in high risk (n = 114); low risk hazard ratio (HR) 1 (reference group), medium risk HR 1.95 (95% CI 1.38-2.74), high risk HR 4.84 (95% CI 3.16-7.43); P < 0.0001. The LEP index was validated in a cohort of 127 Italian patients treated with lenvatinib. While the same classification did not show a prognostic value in a cohort of 311 patients treated with sorafenib, we also show a possible predictive role in favor of lenvatinib in the low risk group.
Conclusions: LEP index is a promising, easy-to-use tool that may be used to stratify patients undergoing systemic treatment of advanced HCC.
Competing Interests: Disclosure The authors have declared no conflicts of interest. Data sharing Data are available upon reasonable request.
(Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)