Prognostic value of European LeukemiaNet 2022 criteria and genomic clusters using machine learning in older adults with acute myeloid leukemia
Silvia Park,
Tong Yoon Kim,
Byung-Sik Cho,
Daehun Kwag,
Jong-Mi Lee,
MyungShin Kim,
Yonggoo Kim,
Jamin Koo,
Anjali Raman,
Tae Kon Kim,
Hee-Je Kim
Affiliations
Silvia Park
Department of Hematology, Catholic Hematology Hospital, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea; Leukemia Research Institute, College of Medicine, The Catholic University of Korea, Seoul, Korea; Division of Hematology/Oncology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
Tong Yoon Kim
Department of Hematology, Catholic Hematology Hospital, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea; Leukemia Research Institute, College of Medicine, The Catholic University of Korea, Seoul
Byung-Sik Cho
Department of Hematology, Catholic Hematology Hospital, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea; Leukemia Research Institute, College of Medicine, The Catholic University of Korea, Seoul
Daehun Kwag
Department of Hematology, Catholic Hematology Hospital, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea; Leukemia Research Institute, College of Medicine, The Catholic University of Korea, Seoul
Jong-Mi Lee
Department of Laboratory Medicine, College of Medicine, The Catholic University of Korea, Seoul
MyungShin Kim
Department of Laboratory Medicine, College of Medicine, The Catholic University of Korea, Seoul
Yonggoo Kim
Department of Laboratory Medicine, College of Medicine, The Catholic University of Korea, Seoul
Jamin Koo
Department of Chemical Engineering, Hongik University, Seoul, Korea; ImpriMedKorea Inc, Seoul
Anjali Raman
Division of Hematology/Oncology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University, Nashville, TN
Tae Kon Kim
Division of Hematology/Oncology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University, Nashville, TN
Hee-Je Kim
Department of Hematology, Catholic Hematology Hospital, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea; Leukemia Research Institute, College of Medicine, The Catholic University of Korea, Seoul
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.
