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. 2021 Jan 7;124(6):1150–1159. doi: 10.1038/s41416-020-01216-6

Fig. 5. Model performance for prediction of BCE and non-BCE.

Fig. 5

a Classification model was developed using logistic regression to predict BCE and non-BCE using two input variables, one comprising of cluster 2 and 4, and the other comprising of cluster 5 and 6. The model had a sensitivity of 77%, specificity of 79% with an error rate of 21.6% and AUC of 0.785. The AUC in the leave one out cross-validation was 0.739. b Escore was developed from the classification model and binary Escore was used for log-rank analysis and data represented using Kaplan–Meier plots.