A new model to estimate duration of survival in patients with hepatocellular carcinoma with BCLC intermediate stage

Abstract

It is difficult to determine whether an individual therapy contributes to the elongation of survival because of the difficulty of organizing clinical research in patients who receive multiple treatments in HCC. We aimed to establish a new model of survival prediction in patients with intermediate stage HCC to establish standards in the recent and coming multi-MTA era. This analysis was prepared using a data set of 753 patients diagnosed HCC prior to 2017. Multiple regression analysis showed age, naïve or recurrence, the size of the largest tumor nodule, the number of nodules, total bilirubin, albumin and α-fetoprotein as independent predictors of survival. A Weibull model had the best fit and, based on these predictors, we established a new predicted survival model. The survival duration can be predicted the proposed model; EXP (4.02580 + (- 0.0086253) × age + (- 0.34667) × (naïve/recurrence) + (- 0.034962) × (number of nodules) + (- 0.079447) × (the size of the largest nodule) + (- 0.21696) × (total bilirubin) + 0.27912 × (albumin) + (- 0.00014741) × (α-fetoprotein)) × (- natural logarithm(0.5))^0.67250. This model is useful for the planning and evaluating the efficacy of recent sequential therapies in multi-MTA era.

Figure 1

Kaplan–Meier curves for overall survival in this cohort study.

Figure 2

Estimation of parametric model. Probability plots for each distribution. The linear course indicates the graph of log–log survival against the log of failure time in each distribution. The dot-to-dot linear showed the survival distribution.