Fig. 4 | Scientific Reports

Fig. 4

From: Machine learning-based construction of a programmed cell death-related model reveals prognosis and immune infiltration in pancreatic adenocarcinoma patients

Fig. 4

Unsupervised clustering and construction of a nomogram model in the TCGA-PAAD cohort. (A) Unsupervised consensus clustering divided patients into two clusters. (B) The optimal number of clusters was determined to be k = 2. (C) Kaplan-Meier survival analysis comparing patients in clusters C1 and C2. (D) Heatmap showing the distribution of PCDRGs expression levels and clinicopathological characteristics across clusters. (E) Univariate Cox regression analysis of risk score and clinicopathological characteristics in the TCGA-PAAD cohort. (F) Multivariate Cox regression analysis of the same variables. (G) Nomogram constructed to predict 1-, 3-, and 5-year overall survival (OS) rate in PAAD patients. (H) Calibration curves evaluating the predictive accuracy of the nomogram. (I) Kaplan-Meier survival curves for patients stratified by nomogram scores. (J) Receiver operating characteristic (ROC) curves assessing the predictive performance of the nomogram for clinicopathological features. (K) ROC curves evaluating the predictive accuracy of the nomogram for 1-, 3-, and 5-year OS.

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