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WHO/ICC Classification for Myelodysplastic Neoplasms/Syndromes Performs Better for Subtype Cytomorphological Diagnosis?

Authors :
Ana Isabel Vicente
Irene Luna
Juan Carlos Ruiz
María José Remigia
Andrés Jerez
Rafael Lluch
Inmaculada Llopis
María Josefa Marco
Carmen Benet
Carmen Alonso
María Dolores Linares
Luis Serrano
María Teresa Orero
Francisco José Ortuño
María Leonor Senent
Source :
Diagnostics, Vol 14, Iss 15, p 1631 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

The International Consensus Classification of Myeloid Neoplasms and Acute Leukemias (ICC) and the 5th edition of the WHO classification (WHO 2022) have refined the diagnosis of myelodysplastic syndromes (MDS). Both classifications segregate MDS subtypes based on molecular or cytogenetic findings but rely on the subjective assessment of blast cell percentage and dysplasia in hematopoietic cell lineages. This study aimed to evaluate interobserver concordance among 13 cytomorphologists from eight hospitals in assessing blast percentages and dysplastic features in 44 MDS patients. The study found fair interobserver agreement for the PB blast percentage and moderate agreement for the BM blast percentage, with the best concordance in cases with 10% BM blasts. Monocyte count agreement was fair, and dysplasia assessment showed moderate concordance for megakaryocytic lineage but lower concordance for erythroid and granulocytic lineages. Overall, interobserver concordance for MDS subtypes was moderate across all classifications, with slightly better results for WHO 2022. These findings highlight the ongoing need for morphological evaluation in MDS diagnosis despite advances in genetic and molecular techniques. The study supports the blast percentage ranges established by the ICC but suggests refining BM blast cutoffs. Given the moderate interobserver concordance, a unified classification approach for MDS is recommended.

Details

Language :
English
ISSN :
20754418
Volume :
14
Issue :
15
Database :
Directory of Open Access Journals
Journal :
Diagnostics
Publication Type :
Academic Journal
Accession number :
edsdoj.63cbac26f42f403d836b3153465f9bfd
Document Type :
article
Full Text :
https://doi.org/10.3390/diagnostics14151631