Fig. 6: Constructing BCR-related prognostic models. | npj Digital Medicine

Fig. 6: Constructing BCR-related prognostic models.

From: Integrative machine learning models predict prostate cancer diagnosis and biochemical recurrence risk: Advancing precision oncology

Fig. 6: Constructing BCR-related prognostic models.

A Screening of prognosis-related genes by univariate Cox analysis. B Genes were screened through lasso/stepwise regression, and a model was constructed using multivariate Cox analysis. C ROC curve analysis of the model’s predictive ability for BCR-related prognosis in the entire dataset. D The Kaplan-Meier survival curves for the high-risk and low-risk groups in the entire dataset. E Risk factor plot of the test dataset. F Risk factor plot of the train dataset. G ROC curve analysis of the model’s predictive ability for BCR-related prognosis in patients within the test dataset. H The Kaplan-Meier survival curves for the high-risk and low-risk groups in the test dataset. I ROC curve analysis of the model’s predictive ability for BCR-related prognosis in patients within the train dataset. J The Kaplan-Meier survival curves for the high-risk and low-risk groups in the train dataset.

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