Fig. 1

Prognostic factor selection using the least absolute shrinkage and selection operator (LASSO) Cox regression model. a Tuning parameter (λ) selection in the LASSO model used tenfold cross-validation via minimum criteria. The partial likelihood deviance curve was plotted versus log(λ). Dotted vertical lines were drawn at the optimal values by using the minimum criteria and the one standard error of the minimum criteria (the 1-SE criteria). A λ value of 0.1201, with log (λ), − 2.1193 was chosen (1-SE criteria) according to tenfold cross-validation. b LASSO coefficient profiles of the 12 prognostic factors. A coefficient profile plot was produced against the log (λ) sequence. A vertical line was drawn at the value selected using tenfold cross-validation, where optimal λ resulted in six nonzero coefficients