Statistical Analysis
StataTM Statistical Software v. 14 (StataCorp, College Station, Texas) was used for consolidation, uniform recording and basic descriptive statistics. Survival analyses and output graphics were conducted with R Statistical Environment v. 3.5.2 (R Core Team, Vienna, Austria). The Kaplan-Meier procedure was used to estimate overall survival (OS) curves and survival at specific time points (1, 2 and 5 years) with associated 95% confidence intervals (26, 27). The log-rank test was applied to assess the existence of significant differences between survival curves in different subgroups. Multivariate Cox regression models were fitted to analyse the association of the OS and the event-free survival (EFS) with a series of potential prognostic factors (28). Non-linear effects were analysed by introducing the relevant predictors as penalised smoothing splines (29). This method was employed to assess whether there may be an age threshold beyond which patients had a less favourable outcome and also to establish a similar threshold for serum AFP level at diagnosis, which influenced OS or EFS. The Spearman test was used to establish an association between ordinal variables, in this case SES and stage. The proportional hazards assumption was tested by computing the scaled Schoenfeld Residuals test (30). A p-value <5% was used as a cut-off to define statistical significance. P-values for relative hazards were calculated in a post-hoc analysis comparing patients with AFP levels above and below the identified thresholds in a Cox model controlling for all other potential confounding factors.