• Most (78%) patients >60 years with newly diagnosed AML who are treated with lower-intensity treatment (LIT) have 2022 ELN adverse-risk.

  • The Beat-AML 2024 risk model incorporates IDH2, KRAS, MLL2 and TP53 to refine risk stratification among patients >60 years given LIT.

While the 2022 European LeukemiaNet (ELN) acute myeloid leukemia (AML) risk classification reliably predicts outcomes in younger patients treated with intensive chemotherapy, it is unclear whether it applies to adults ≥ 60 years treated with lower-intensity treatment (LIT). We aimed to test the prognostic impact of ELN risk in patients with newly diagnosed (ND) AML ≥ 60 years given LIT and to further refine risk stratification for these patients. A total of 595 patients were included: 11% had favorable-risk, 11% had intermediate-risk, and 78% had adverse-risk AML as defined by ELN. ELN risk was prognostic for overall survival (OS) (P<0.001) but did not stratify favorable-risk from intermediate-risk (P=0.71). Within adverse-risk AML, the impact of additional molecular abnormalities was further evaluated. Multivariable analysis was performed on a training set (N=316) and identified IDH2 mutation as an independent favorable prognostic factor, and KRAS, MLL2, and TP53 mutations as unfavorable (P<0.05). A "mutation-score" was calculated for each combination of these mutations, assigning adverse-risk patients into two risk groups: -1 to 0 points ("Beat-AML-intermediate") vs 1+ points ("Beat-AML-adverse"). In the final refined risk classification, the ELN favorable- and intermediate-risk groups were combined into a newly defined "Beat-AML-favorable-risk", in addition to mutation scoring within the ELN adverse-risk. This approach redefines risk for older ND AML and proposes refined Beat-AML-favorable- (22%), Beat-AML-intermediate- (41%), and Beat-AML-adverse-risk (37%) groups with improved discrimination for OS (2-year OS: 48% vs 33% vs 11%, respectively, P<0.001; C-index: 0.60 vs 0.55 for ELN), providing patients and providers additional information for treatment decision-making.

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