Advanced hepatocellular carcinoma: Which staging systems best predict prognosis?

Abstract

Purpose: The purpose of cancer staging systems is to accurately predict patient prognosis. The outcome of advanced hepatocellular carcinoma (HCC) depends on both the cancer stage and the extent of liver dysfunction. Many staging systems that include both aspects have been developed. It remains unknown, however, which of these systems is optimal for predicting patient survival. Patients and Methods: Patients with advanced HCC treated over a 5-year period at Memorial Sloan-Kettering Cancer Center were identified from an electronic medical record database. Patients with sufficient data for utilization in all staging systems were included. TNM sixth edition, Okuda, Barcelona Clinic Liver Cancer (BCLC), Cancer of the Liver Italian Program (CLIP), Chinese University Prognostic Index (CUPI), Japan Integrated Staging (JIS), and Groupe d'Etude et de Traitement du Carcinome Hepatocellulaire (GETCH) systems were ranked on the basis of their accuracy at predicting survival by using concordance index (c-index). Other independent prognostic variables were also identified. Results: Overall, 187 eligible patients were identified and were staged by using the seven staging systems. CLIP, CUPI, and GETCH were the three top-ranking staging systems. BCLC and TNM sixth edition lacked any meaningful prognostic discrimination. Performance status, AST, abdominal pain, and esophageal varices improved the discriminatory ability of CLIP. Conclusion: In our selected patient population, CLIP, CUPI, and GETCH were the most informative staging systems in predicting survival in patients with advanced HCC. Prospective validation is required to determine if they can be accurately used to stratify patients in clinical trials and to direct the appropriate need for systemic therapy versus best supportive care. BCLC and TNM sixth edition were not helpful in predicting survival outcome, and their use is not supported by our data. © 2010 by American Society of Clinical Oncology.