Implications of the 5 th Edition of the World Health Organization Classification and International Consensus Classification of Myeloid Neoplasm in Myelodysplastic Syndrome With Excess Blasts and Acute Myeloid Leukemia.
Cheonghwa LeeHa Nui KimJung Ah KwonSoo-Young YoonMin Ji JeonEun Sang YuDea Sik KimChul Won ChoiJung YoonPublished in: Annals of laboratory medicine (2023)
The fifth edition of the WHO classification (2022 WHO) and the International Consensus Classification (2022 ICC) of myeloid neoplasms have been recently published. We reviewed the changes in the diagnosis distribution in patients with MDS with excess blasts (MDS-EB) or AML using both classifications. Forty-seven patients previously diagnosed as having AML or MDS-EB with available mutation analysis data, including targeted next-generation and RNA-sequencing data, were included. We reclassified 15 (31.9%) and 27 (57.4%) patients based on the 2022 WHO and 2022 ICC, respectively. One patient was reclassified as having a translocation categorized as a rare recurring translocation in both classifications. Reclassification was mostly due to the addition of mutation-based diagnostic criteria (i.e., AML, myelodysplasia-related) or a new entity associated with TP53 mutation. In both classifications, MDS diagnosis required the confirmation of multi-hit TP53 alterations. Among 14 patients with TP53 mutations, 11 harbored multi-hit TP53 alterations, including four with TP53 mutations and loss of heterozygosity. Adverse prognosis was associated with multi-hit TP53 alterations ( P =0.009) in patients with MDS-EB, emphasizing the importance of detecting the mutations at diagnosis. The implementation of these classifications may lead to the identification of different subtypes from previously heterogeneous diagnostic categories based on genetic characteristics.
Keyphrases
- acute myeloid leukemia
- end stage renal disease
- machine learning
- deep learning
- ejection fraction
- chronic kidney disease
- newly diagnosed
- peritoneal dialysis
- prognostic factors
- primary care
- dendritic cells
- randomized controlled trial
- big data
- dna methylation
- healthcare
- single cell
- immune response
- patient reported outcomes
- electronic health record
- case report
- emergency department
- gene expression
- cancer therapy
- artificial intelligence
- genome wide
- patient reported
- quality improvement
- meta analyses
- adverse drug