Fig. 5
From: Pathway-based subnetworks enable cross-disease biomarker discovery
PIK3CA signaling predictor of breast cancer recurrence. a Independent validation of prognostic model trained on SIMMS’ risk scores and clinical covariates (N and tumor size). Risk score estimates were grouped into quartiles derived from the TEAM training cohort; each group was compared against Q1. Hazard ratios were estimated using Cox proportional hazards model and significance of survival difference was estimated using the log-rank test assessing heterogeneity across the four groups. b Distribution of patient risk scores in the TEAM Validation cohort (top panel). Bottom panel shows the predicted 5-year recurrence probabilities (solid line) and 95% CI (dashed lines) as a function of patient risk score. Vertical dashed black line indicates training set median risk score. c Risk prediction by the IHC4 protein model in the TEAM validation cohort. Quartiles were defined in the training cohort and applied to the validation cohort. Quartiles Q2-Q4 were compared against Q1, with adjustment for age, nodal status, tumor size and grade using Cox proportional hazards modeling and the log-rank test. d Comparison of SIMMS’ modules model (PIK3CA risk predictor) and IHC4-protein model using area under the receiver operating characteristic (AUC) curve as performance indicator.
