Abstract
Several systems (tumor-node-metastasis [TNM], Barcelona Clinic Liver Cancer [BCLC], Okuda, Cancer of the Liver Italian Program [CLIP], and albumin-bilirubin grade [ALBI]) were developed to estimate the prognosis of patients with hepatocellular carcinoma (HCC) mostly prior to the prevalent use of sorafenib. We aimed to compare the prognostic and discriminatory power of these models in predicting survival for HCC patients treated with sorafenib and to identify independent prognostic factors for survival in this population. Patients who received sorafenib for the treatment of HCC between 1 January 2008 and 30 June 2015 in the provinces of British Columbia and Alberta, and two large cancer centers in Toronto, Ontario, were included. Survival was assessed using the Kaplan-Meier method. Multivariate Cox regression was used to identify predictors of survival. The models were compared with respect to homogeneity, discriminatory ability, monotonicity of gradients, time-dependent area under the curve, and Akaike information criterion. A total of 681 patients were included. 80% were males, 86% had Child-Pugh class A, and 37% of patients were East Asians. The most common etiology for liver disease was hepatitis B (34%) and C (31%). In all model comparisons, CLIP performed better while BCLC and TNM7 performed less favorably but the differences were small. The utility of each system in allocating patients into different prognostic groups varied, for example, TNM poorly differentiated patients in advanced stages (8.7 months (m) (95% CI 6.5-11.5) versus 8.4 m (95% CI 7.0-9.6) for stages III and IV, respectively) while ALBI had excellent discrimination of early grades (15.6 m [95% CI 13.0-18.4] versus 8.3 m [95% CI 7.0-9.2] for grades 1 and 2, respectively). On multivariate analysis, hepatitis C, alcoholism, and prior hepatic resection were independently prognostic of better survival (P < 0.01). In conclusion, none of the prognostic systems was optimal in predicting survival in sorafenib-treated patients with HCC. Etiology of liver disease should be considered in future models and clinical trial designs.