Figure 3.
Kaplan-Meier estimates of PFS by genetic subgroups and treatment. (A) Kaplan-Meier estimates of PFS according to the hierarchical model of genomic aberrations, color-coded based on chromosomal aberration for GClb (left) and VenG (right). (B) Kaplan-Meier plots for PFS based on the status for del(17p) (presence vs absence), TP53 (mutated vs unmutated), and IGHV (unmutated vs mutated) and (C) for ATM, NOTCH1, SF3B1, and BIRC3 (mutated vs unmutated) for both treatment groups (green: VenG, blue: GClb). Subgroups with mutation/aberration are depicted by solid lines, subgroups with wild-type by dashed lines (B, C). HR values were calculated by cox proportional hazards, P values by log-rank test.

Kaplan-Meier estimates of PFS by genetic subgroups and treatment. (A) Kaplan-Meier estimates of PFS according to the hierarchical model of genomic aberrations, color-coded based on chromosomal aberration for GClb (left) and VenG (right). (B) Kaplan-Meier plots for PFS based on the status for del(17p) (presence vs absence), TP53 (mutated vs unmutated), and IGHV (unmutated vs mutated) and (C) for ATM, NOTCH1, SF3B1, and BIRC3 (mutated vs unmutated) for both treatment groups (green: VenG, blue: GClb). Subgroups with mutation/aberration are depicted by solid lines, subgroups with wild-type by dashed lines (B, C). HR values were calculated by cox proportional hazards, P values by log-rank test.

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