Prognostic prediction models for postoperative patients with stage I to III colorectal cancer based on machine learning

Figure 4 Prediction of recurrence-free survival by machine learning models. The plots show the areas under the curve (AUCs) and their 95%CI. A: The linear regression (LR) model in the training set [class 1 (cl 1): Before: 0.84 (0.76-0.91), after: 0.76 (0.67-0.84); class 2 (cl 2): Before: 0.88 (0.81-0.93), after: 0.76 (0.66-0.85); class 3 (cl 3): Before: 0.99 (0.96-1.00), after: 0.95 (0.89-0.98)]; B: The LR model in the testing set [cl 1: Before: 0.80 (0.65-0.92), after: 0.68 (0.53-0.82); cl 2: Before: 0.76 (0.53-0.92), after: 0.66 (0.44-0.82); cl 3: Before: 0.95 (0.88-1.00), after: 0.85 (0.66-0.97)]; C: The linear discriminant analysis (LDA) model in the training set [cl 1: Before: 0.84 (0.76-0.91), after: 0.76 (0.67-0.84); cl 2: Before: 0.86 (0.79-0.92), after: 0.75 (0.64-0.85); cl 3: Before: 0.97 (0.92-1.00), after: 0.93 (0.88-0.98)]; D: The LDA model in the testing set [cl 1: Before: 0.83 (0.69-0.93), after: 0.70 (0.56-0.85); cl 2: Before: 0.77 (0.57-0.93), after: 0.67 (0.46-0.83); cl 3: Before: 0.92 (0.83-0.99), after: 0.85 (0.65-0.98)]; E: The eXtreme gradient boosting (XGBoost) model in the training set [cl 1: Before: 0.93 (0.86-0.97), after: 0.89 (0.82-0.94); cl 2: Before: 0.92 (0.85-0.97), after: 0.84 (0.75-0.92); cl 3: Before: 0.96 (0.91-1.00), after: 0.94 (0.86-1.00)]; F: The XGBoost model in the testing set [cl 1: Before: 0.81 (0.65-0.93), after: 0.83 (0.68-0.95); cl 2: Before: 0.70 (0.47-0.87), after: 0.70 (0.45-0.87); cl 3: Before: 0.79 (0.56-0.96), after: 0.88 (0.75-0.97)]; G: The categorical features and gradient boosting (CatBoost) model in the training set [cl 1: Before: 0.95 (0.91-0.99), after: 0.87 (0.79-0.93); cl 2: Before: 0.93 (0.87-0.97), after: 0.82 (0.72-0.91); cl 3: Before: 0.96 (0.90-1.00), after: 0.88 (0.73-1.00)]; and H: The CatBoost model in the testing set [cl 1: Before: 0.82 (0.67-0.93), after: 0.79 (0.64-0.91); cl 2: Before: 0.72 (0.51-0.90), after: 0.68 (0.45-0.85); cl 3: Before: 0.83 (0.67-0.96), after: 0.84 (0.68-0.93)]. The curves of the models constructed with the full-variable datasets and the datasets containing only important variables are depicted with solid lines and dashed lines, respectively (abbreviated as “before” and “after” in this annotation).