Evidence-Based Diagnosis, Staging, and Treatment of Patients With Hepatocellular Carcinoma

Gastroenterology. 2016 Apr;150(4):835-53. doi: 10.1053/j.gastro.2015.12.041. Epub 2016 Jan 12.


Evidence-based management of patients with hepatocellular carcinoma (HCC) is key to their optimal care. For individuals at risk for HCC, surveillance usually involves ultrasonography (there is controversy over use of biomarkers). A diagnosis of HCC is made based on findings from biopsy or imaging analyses. Molecular markers are not used in diagnosis or determination of prognosis and treatment for patients. The Barcelona Clinic Liver Cancer algorithm is the most widely used staging system. Patients with single liver tumors or as many as 3 nodules ≤3 cm are classified as having very early or early-stage cancer and benefit from resection, transplantation, or ablation. Those with a greater tumor burden, confined to the liver, and who are free of symptoms are considered to have intermediate-stage cancer and can benefit from chemoembolization if they still have preserved liver function. Those with symptoms of HCC and/or vascular invasion and/or extrahepatic cancer are considered to have advanced-stage cancer and could benefit from treatment with the kinase inhibitor sorafenib. Patients with end-stage HCC have advanced liver disease that is not suitable for transplantation and/or have intense symptoms. Studies now aim to identify molecular markers and imaging techniques that can detect patients with HCC at earlier stages and better predict their survival time and response to treatment.

Keywords: BCLC; Early Detection; Liver Cancer; Therapy.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Algorithms
  • Carcinoma, Hepatocellular / mortality
  • Carcinoma, Hepatocellular / pathology*
  • Carcinoma, Hepatocellular / therapy*
  • Disease Progression
  • Evidence-Based Medicine*
  • Humans
  • Liver Neoplasms / mortality
  • Liver Neoplasms / pathology*
  • Liver Neoplasms / therapy*
  • Neoplasm Staging
  • Patient Selection
  • Predictive Value of Tests
  • Risk Factors
  • Time Factors
  • Treatment Outcome