Beat-AML 2024 ELN–refined risk stratification for older adults with newly diagnosed AML given lower-intensity therapy

•Most (78%) patients aged ≥ 60 years with ND AML treated with LIT are classified as having 2022 ELN adverse risk.•The Beat-AML 2024 risk model incorporates IDH2, KRAS, MLL2, and TP53 to refine risk stratification among patients aged ≥ 60 years given LIT. [Display omitted] Although 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 aged ≥60 years given LIT and to further refine risk stratification for these patients. A total of 595 patients were included: 11% had favorable-, 11% intermediate-, and 78% had adverse-risk AML. ELN risk was prognostic for overall survival (OS) (P < .001) but did not stratify favorable- from intermediate-risk (P = .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 < .05). A “mutation score” was calculated for each combination of these mutations, assigning adverse-risk patients to 2 risk groups: −1 to 0 points (“Beat-AML intermediate”) vs 1+ points (“Beat-AML adverse”). In the final refined risk classification, ELN favorable- and intermediate-risk were combined into a newly defined “Beat-AML favorable-risk” group, in addition to mutation scoring within the ELN adverse-risk group. This approach redefines risk for older patients with ND AML and proposes refined Beat-AML risk groups with improved discrimination for OS (2-year OS, 48% vs 33% vs 11%, respectively; P < .001), providing patients and providers additional information for treatment decision-making.