Prognostic value of European LeukemiaNet 2022 criteria and genomic clusters using machine learning in older adults with acute myeloid leukemia

Haematologica. 2024 Apr 1;109(4):1095-1106. doi: 10.3324/haematol.2023.283606.

Abstract

This study aimed to validate the new European Leukemia Net (ELN) 2022 criteria for genetic risk stratification in older adults with acute myeloid leukemia (AML) and to determine the most likely set of clusters of similar cytogenetic and mutation properties correlated with survival outcomes in three treatment groups: intensive chemotherapy (IC), hypomethylating agents (HMA) alone, and HMA plus venetoclax (HMA/VEN). The study included 279 patients (aged ≥60 years) who received IC (N=131), HMA (N=76), and HMA/VEN (N=72) between July 2017 and October 2021. No significant differences were observed in survival among the groups according to ELN 2022 risk stratification. Unsupervised hierarchical clustering analysis identified nine genomic clusters (C1-9) with varying survival outcomes depending on treatment type. For example, C4 (predominant for core binding factor-AML) displayed a favorable prognosis in the IC group, but not in the HMA or HMA/VEN groups. The HMA/VEN group had better outcomes than the HMA group in many clusters (C1, 2, 3, and 5); however, the addition of VEN to HMA or IC did not improve the survival outcomes compared with those of HMA alone in C7 and C9 (predominant for -5, del(5q), -7, -17/abn(17p), complex karyotypes, and mutated TP53). The study highlights the limitations of ELN genetic risk stratification in older adults with AML. It emphasizes the need for a more comprehensive approach that considers co-occurring somatic mutations to guide treatment selection in older adults with AML.

MeSH terms

  • Aged
  • Antineoplastic Combined Chemotherapy Protocols / therapeutic use
  • Bridged Bicyclo Compounds, Heterocyclic
  • Genomics
  • Humans
  • Leukemia, Myeloid, Acute* / diagnosis
  • Leukemia, Myeloid, Acute* / drug therapy
  • Leukemia, Myeloid, Acute* / genetics
  • Machine Learning
  • Prognosis
  • Retrospective Studies
  • Risk Factors

Substances

  • Bridged Bicyclo Compounds, Heterocyclic

Grants and funding

Funding: This research was supported by the Research Fund of Seoul St. Mary’s Hospital associated with The Catholic University of Korea and by a grant from Catholic Institute of Cell Therapy in 2023; by a grant from the National Research Foundation of Korea funded by the South Korean government (MSIT; 2022R1A2C2004517) and a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health and Welfare, Republic of Korea (HI22C1314).