Machine Learning Developed a Programmed Cell Death Signature for Predicting Prognosis, Ecosystem, and Drug Sensitivity in Ovarian Cancer

Figure 3

Evaluation of the performance of CDS in predicting the clinical outcome of OC patients. ((a) and (b)) Univariate and multivariate Cox regression analysis considering grade, stage, and CDS in training and testing cohort. (c) C-index of CDS and other 54 established signatures in evaluating the prognosis of OC patients. (d) Predictive nomogram constructed using CDS, grade, and stage. ((e) and (f)) Calibration and ROC curve evaluating the predictive value of nomogram in the overall survival rate of OC patients. (g) DCA demonstrating the good potential of the nomogram for clinical application.

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