Analyses of PFS
CRPS
The RSF analyses with clinical variables and conventional PET parameters for PFS using the training set resulted in an out-of-bag (OOB) error rate of 49.2%. On the other hand, Δcode similarity (texture feature coding co-occurrence), Δinverse difference moment (texture feature coding co-occurrence), mean SUVImportance of each radiomic PET variable in predicting PFS.The CRPS of the predictive model for PFS with clinical variables and conventional PET parameters was 0.165 when using the training set and 0.199 when using the test set. In addition, the CRPS of the predictive model for PFS with clinical variables and selected radiomic PET parameters was 0.128 when using the training set and 0.200 when using the test set. The time-dependent BS for each prediction model is provided in Fig. Time-dependent Brier score (BS; mean-squared error) curve of random survival forest models to predict of progression-free survival (PFS). (