A real-world analysis of clinical outcomes in AML with myelodysplasia-related changes: a comparison of ICC and WHO-HAEM5 criteria.
Qianghua ZhouDavidson ZhaoMojgan ZarifMarta B DavidsonMark D MindenAnne TierensYu Wing Tony YeungCuihong WeiHong ChangPublished in: Blood advances (2024)
The proposed fifth edition of the World Health Organization classification of hematolymphoid tumors (WHO-HAEM5) and International Consensus Classification (ICC) provide different definitions of acute myeloid leukemia with myelodysplasia-related genetics (AML-MR). We conducted a retrospective study which included a cohort of 432 patients, with 354 patients fulfilling WHO-HAEM5 criteria for WHO-AML-MR or 276 patients fulfilling ICC criteria for ICC-AML-MR by gene mutation or cytogenetics (ICC-AML-MR-M/CG). The clinicopathological features were largely similar, irrespective of the classification used, except for higher rates of complex karyotype, monosomy 17, TP53 mutations, and fewer RUNX1 mutations in the WHO-AML-MR group. TP53 mutations were associated with distinct clinicopathological features and dismal outcomes (hazard ratio [HR], 2.98; P < .001). ICC-AML-MR-M/CG group had superior outcome compared with the WHO-AML-MR group (HR, 0.80, P = .032), largely in part due to defining TP53 mutated AML as a standalone entity. In the intensively-treated group, WHO-AML-MR had significantly worse outcomes than AML by differentiation (HR, 1.97; P = .024). Based on ICC criteria, ICC-AML-MR-M/CG had more inferior outcomes compared to AML not otherwise specified (HR, 2.11; P = .048 and HR, 2.55; P = .028; respectively). Furthermore, changing the order of genetic abnormalities defining AML-MR (ie, by gene mutations or cytogenetics) did not significantly affect clinical outcomes. ICC-AML-MR-M/CG showed similar outcomes regardless of the order of assignment. We propose to harmonize the 2 classifications by excluding TP53 mutations from WHO-HAEM5 defined AML-MR group and combining AML-MR defined by gene mutations and cytogenetics to form a unified group.
Keyphrases
- acute myeloid leukemia
- allogeneic hematopoietic stem cell transplantation
- contrast enhanced
- magnetic resonance
- machine learning
- end stage renal disease
- chronic kidney disease
- deep learning
- type diabetes
- magnetic resonance imaging
- gene expression
- metabolic syndrome
- prognostic factors
- peritoneal dialysis
- computed tomography
- genome wide
- insulin resistance
- copy number
- glycemic control