Precision assessment of the model created using DALPMs
The model's verification involved a comprehensive assessment of the risk score determined by the model. Initially, we employed principal component analysis (PCA) with the assistance of the R package ‘scatterplot3d’ to visually represent the distinction between DALPMs and other variables in relation to patients categorized as high and low risks, then employed the R libraries ‘survival’ and “survminer” to determined possible variations in overall survival (OS) and progression-free survival (PFS) among individuals with varying risk scores. Furthermore, the risk score underwent independent prognostic analysis through univariate and multivariate Cox analyses using the R package “survival.” We generated Receiver Operating Characteristic (ROC) curves utilizing the R packages “survival,” “survminer,” and “timeROC” to assess the precision of our risk scores in predicting patient outcomes. For the same objective, the C-index analysis was conducted utilizing the R packages “dplyr,” “survival,” “rms,” and “pec.”