Fig. 4
From: A high-risk, Double-Hit, group of newly diagnosed myeloma identified by genomic analysis
A recursive partitioning model for PFS and OS identified clinical and genomic markers associated with risk. a A recursive partitioning model for PFS based on the inclusion of genetic and clinical predictors, showing the terminal nodes. b Kaplan–Meier curves were generated for PFS for all terminal nodes of the tree. c Nodes with similar outcome profiles were combined to generate three risk groups. Nodes 8 and 18 were combined to designate low-risk patients (green); nodes 11, 19, and 6 were combined to designate intermediate-risk patients (red); nodes 10 and 7 were combined to designate Double-Hit patients (blue). Double-Hit comprised 6.1% of the total patient population and included patients who were either of the following: bi-allelic inactivation of TP53 or ISS stage III with amplification of CKS1B. Significant differences in PFS between the risk groups are identified (P < 0.0001). d As in (c) with OS. e The risk groups identified in (c) were applied to a subset of Total Therapy patients (n = 85) with available genetic data; significantly different PFS outcomes are observed, with especially poor PFS in Double-Hit patients (P < 0.0001). f As in (e) with OS
