Fig. 2

Prognostic model based on radiomic profile in HGSOC. a Summary of univariate Cox regression between each radiomic feature and overall survival in the discovery set. Each black point represents the p value (y-axis) and hazard ratio (HR; x-axis) of a radiomic feature. Red horizontal dashed line indicates the false discovery rate (FDR) of 0.05; red vertical dashed line indicates HR of 1. b Least absolute shrinkage and selection operator (LASSO) regression analysis was performed to select radiomic features for prognostic model-building for HGSOC patients. Feature coefficients were plotted against shrinkage parameter (Lambda). c Partial likelihood deviance from Cox regression (y-axis) was generated under different shrinkage parameters (x-axis). Number of features selected corresponding to each lambda are given above the plot. Kaplan−Meier analyses were performed between radiomic prognostic vector (RPV) and overall survival in d HH discovery cohort (n = 136), e TCGA validation cohort (n = 70) and f HH validation cohort (n = 77). Red line, RPV low; green line, RPV medium; blue line, RPV high. p values are given by log-rank test. HGSOC high-grade serous ovarian cancer, TCGA the Cancer Genome Atlas