Novel biomarker-based model for the prediction of sorafenib response and overall survival in advanced hepatocellular carcinoma: a prospective cohort study.

Journal Article (Journal Article)

BACKGROUND: Prediction of the outcome of sorafenib therapy using biomarkers is an unmet clinical need in patients with advanced hepatocellular carcinoma (HCC). The aim was to develop and validate a biomarker-based model for predicting sorafenib response and overall survival (OS). METHODS: This prospective cohort study included 124 consecutive HCC patients (44 with disease control, 80 with progression) with Child-Pugh class A liver function, who received sorafenib. Potential serum biomarkers (namely, hepatocyte growth factor [HGF], fibroblast growth factor [FGF], vascular endothelial growth factor receptor-1, CD117, and angiopoietin-2) were tested. After identifying independent predictors of tumor response, a risk scoring system for predicting OS was developed and 3-fold internal validation was conducted. RESULTS: A risk scoring system was developed with six covariates: etiology, platelet count, Barcelona Clinic Liver Cancer stage, protein induced by vitamin K absence-II, HGF, and FGF. When patients were stratified into low-risk (score ≤ 5), intermediate-risk (score 6), and high-risk (score ≥ 7) groups, the model provided good discriminant functions on tumor response (concordance [c]-index, 0.884) and 12-month survival (area under the curve [AUC], 0.825). The median OS was 19.0, 11.2, and 6.1 months in the low-, intermediate-, and high-risk group, respectively (P < 0.001). In internal validation, the model maintained good discriminant functions on tumor response (c-index, 0.825) and 12-month survival (AUC, 0.803), and good calibration functions (all P > 0.05 between expected and observed values). CONCLUSIONS: This new model including serum FGF and HGF showed good performance in predicting the response to sorafenib and survival in patients with advanced HCC.

Full Text

Duke Authors

Cited Authors

  • Kim, HY; Lee, DH; Lee, J-H; Cho, YY; Cho, EJ; Yu, SJ; Kim, YJ; Yoon, J-H

Published Date

  • March 20, 2018

Published In

Volume / Issue

  • 18 / 1

Start / End Page

  • 307 -

PubMed ID

  • 29558905

Pubmed Central ID

  • PMC5859435

Electronic International Standard Serial Number (EISSN)

  • 1471-2407

Digital Object Identifier (DOI)

  • 10.1186/s12885-018-4211-2

Language

  • eng

Conference Location

  • England