TY - JOUR
T1 - Data-driven, harmonised classification system for myelodysplastic syndromes
T2 - a consensus paper from the International Consortium for Myelodysplastic Syndromes
AU - International Consortium on Myelodysplastic Syndromes
AU - Komrokji, Rami S.
AU - Lanino, Luca
AU - Ball, Somedeb
AU - Bewersdorf, Jan P.
AU - Marchetti, Monia
AU - Maggioni, Giulia
AU - Travaglino, Erica
AU - Al Ali, Najla H.
AU - Fenaux, Pierre
AU - Platzbecker, Uwe
AU - Santini, Valeria
AU - Diez-Campelo, Maria
AU - Singh, Avani
AU - Jain, Akriti G.
AU - Aguirre, Luis E.
AU - Tinsley-Vance, Sarah M.
AU - Schwabkey, Zaker I.
AU - Chan, Onyee
AU - Xie, Zhouer
AU - Brunner, Andrew M.
AU - Kuykendall, Andrew T.
AU - Bennett, John M.
AU - Buckstein, Rena
AU - Bejar, Rafael
AU - Carraway, Hetty
AU - DeZern, Amy E.
AU - Griffiths, Elizabeth A.
AU - Halene, Stephanie
AU - Hasserjian, Robert P.
AU - Lancet, Jeffrey
AU - List, Alan F.
AU - Loghavi, Sanam
AU - Odenike, Olatoyosi
AU - Padron, Eric
AU - Patnaik, Mrinal M.
AU - Roboz, Gail J.
AU - Stahl, Maximilian
AU - Sekeres, Mikkael A.
AU - Steensma, David P.
AU - Savona, Michael R.
AU - Taylor, Justin
AU - Xu, Mina L.
AU - Sweet, Kendra
AU - Sallman, David A.
AU - Nimer, Stephen D.
AU - Hourigan, Christopher S.
AU - Wei, Andrew H.
AU - Sauta, Elisabetta
AU - D'Amico, Saverio
AU - Asti, Gianluca
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/11
Y1 - 2024/11
N2 - The WHO and International Consensus Classification 2022 classifications of myelodysplastic syndromes enhance diagnostic precision and refine decision-making processes in these diseases. However, some discrepancies still exist and potentially cause inconsistency in their adoption in a clinical setting. We adopted a data-driven approach to provide a harmonisation between these two classification systems. We investigated the importance of genomic features and their effect on the cluster assignment process to define harmonised entity labels. A panel of expert haematologists, haematopathologists, and data scientists who are members of the International Consortium for Myelodysplastic Syndromes was formed and a modified Delphi consensus process was adopted to harmonise morphologically defined categories without a distinct genomic profile. The panel held regular online meetings and participated in a two-round survey using an online voting tool. We identified nine clusters with distinct genomic features. The cluster of highest hierarchical importance was characterised by biallelic TP53 inactivation. Cluster assignment was irrespective of blast count. Individuals with monoallelic TP53 inactivation were assigned to other clusters. Hierarchically, the second most important group included myelodysplastic syndromes with del(5q). Isolated del(5q) and less than 5% of blast cells in the bone marrow were the most relevant label-defining features. The third most important cluster included myelodysplastic syndromes with mutated SF3B1. The absence of isolated del(5q), del(7q)/-7, abn3q26.2, complex karyotype, RUNX1 mutations, or biallelic TP53 were the basis for a harmonised label of this category. Morphologically defined myelodysplastic syndrome entities showed large genomic heterogeneity that was not efficiently captured by single-lineage versus multilineage dysplasia, marrow blasts, hypocellularity, or fibrosis. We investigated the biological continuum between myelodysplastic syndromes with more than 10% bone marrow blasts and acute myeloid leukaemia, and found only a partial overlap in genetic features. After the survey, myelodysplastic syndromes with low blasts (ie, less than 5%) and myelodysplastic syndromes with increased blasts (ie, 5% or more) were recognised as disease entities. Our data-driven approach can efficiently harmonise current classifications of myelodysplastic syndromes and provide a reference for patient management in a real-world setting.
AB - The WHO and International Consensus Classification 2022 classifications of myelodysplastic syndromes enhance diagnostic precision and refine decision-making processes in these diseases. However, some discrepancies still exist and potentially cause inconsistency in their adoption in a clinical setting. We adopted a data-driven approach to provide a harmonisation between these two classification systems. We investigated the importance of genomic features and their effect on the cluster assignment process to define harmonised entity labels. A panel of expert haematologists, haematopathologists, and data scientists who are members of the International Consortium for Myelodysplastic Syndromes was formed and a modified Delphi consensus process was adopted to harmonise morphologically defined categories without a distinct genomic profile. The panel held regular online meetings and participated in a two-round survey using an online voting tool. We identified nine clusters with distinct genomic features. The cluster of highest hierarchical importance was characterised by biallelic TP53 inactivation. Cluster assignment was irrespective of blast count. Individuals with monoallelic TP53 inactivation were assigned to other clusters. Hierarchically, the second most important group included myelodysplastic syndromes with del(5q). Isolated del(5q) and less than 5% of blast cells in the bone marrow were the most relevant label-defining features. The third most important cluster included myelodysplastic syndromes with mutated SF3B1. The absence of isolated del(5q), del(7q)/-7, abn3q26.2, complex karyotype, RUNX1 mutations, or biallelic TP53 were the basis for a harmonised label of this category. Morphologically defined myelodysplastic syndrome entities showed large genomic heterogeneity that was not efficiently captured by single-lineage versus multilineage dysplasia, marrow blasts, hypocellularity, or fibrosis. We investigated the biological continuum between myelodysplastic syndromes with more than 10% bone marrow blasts and acute myeloid leukaemia, and found only a partial overlap in genetic features. After the survey, myelodysplastic syndromes with low blasts (ie, less than 5%) and myelodysplastic syndromes with increased blasts (ie, 5% or more) were recognised as disease entities. Our data-driven approach can efficiently harmonise current classifications of myelodysplastic syndromes and provide a reference for patient management in a real-world setting.
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U2 - 10.1016/S2352-3026(24)00251-5
DO - 10.1016/S2352-3026(24)00251-5
M3 - Review article
C2 - 39393368
AN - SCOPUS:85207238699
SN - 2352-3026
VL - 11
SP - e862-e872
JO - The Lancet Haematology
JF - The Lancet Haematology
IS - 11
ER -