A model predicting survival of patients with recurrent or progressive hepatocellular carcinoma: the MORE score.

Choi, Sang Il; Yu, Ami; Kim, Bo Hyun; Ko, Eun Jeong; Park, Soon Seob; Nam, Byung‐Ho; Park, Joong‐Won

Background and Aim Most prognostic models for hepatocellular carcinoma are based on data at the time of diagnosis. However, the disease frequently recurs or progresses after initial treatment, with changes in tumor burden and clinical status. Therefore, we developed a risk score model to predict survival of hepatocellular carcinoma patients at the time of disease recurrence or progression. Methods Of 1972 patients newly diagnosed with hepatocellular carcinoma at the National Cancer Center, Korea, between January 2004 and December 2009, 1301 with recurrent or progressive disease were enrolled. They were randomly classified into a development (75%, n = 976) and a validation cohort (25%, n = 325). A survival prediction method was established in the development cohort using the multivariate Cox proportional hazards model, and its performance was evaluated on the validation cohort. Results A model predicting survival of patients with recurrent or progressive hepatocellular carcinoma was developed using some known independent prognostic factors for overall survival: age, albumin, Model for End-Stage Liver Disease score, tumor burden, serum alpha-fetoprotein level, and presence of ascites. In addition, initial treatment modality and best response after initial treatment were also independent prognostic factors and were incorporated in the model. The C-statistics and χ2 statistics of this novel score for the validation cohort were 0.808 (95% CI: 0.781-0.834) and 4.408 for 3-year survival. Conclusions A new model to predict survival of patients with recurrent or progressive hepatocellular carcinoma was developed and validated. This model may be useful for planning subsequent treatments.

LIVER cancer; DISEASE progression; COHORT analysis; ALPHA fetoproteins; LIVER function tests

Journal of Gastroenterology & Hepatology, 2017, Vol 32, Issue 3, p651

0815-9319

Academic Journal

10.1111/jgh.13532