Data-driven, harmonised classification system for myelodysplastic syndromes: a consensus paper from the International Consortium for Myelodysplastic Syndromes.

IF 15.4 1区 医学 Q1 HEMATOLOGY
Lancet Haematology Pub Date : 2024-11-01 Epub Date: 2024-10-09 DOI:10.1016/S2352-3026(24)00251-5
Rami S Komrokji, Luca Lanino, Somedeb Ball, Jan P Bewersdorf, Monia Marchetti, Giulia Maggioni, Erica Travaglino, Najla H Al Ali, Pierre Fenaux, Uwe Platzbecker, Valeria Santini, Maria Diez-Campelo, Avani Singh, Akriti G Jain, Luis E Aguirre, Sarah M Tinsley-Vance, Zaker I Schwabkey, Onyee Chan, Zhouer Xie, Andrew M Brunner, Andrew T Kuykendall, John M Bennett, Rena Buckstein, Rafael Bejar, Hetty E Carraway, Amy E DeZern, Elizabeth A Griffiths, Stephanie Halene, Robert P Hasserjian, Jeffrey Lancet, Alan F List, Sanam Loghavi, Olatoyosi Odenike, Eric Padron, Mrinal M Patnaik, Gail J Roboz, Maximilian Stahl, Mikkael A Sekeres, David P Steensma, Michael R Savona, Justin Taylor, Mina L Xu, Kendra Sweet, David A Sallman, Stephen D Nimer, Christopher S Hourigan, Andrew H Wei, Elisabetta Sauta, Saverio D'Amico, Gianluca Asti, Gastone Castellani, Mattia Delleani, Alessia Campagna, Uma M Borate, Guillermo Sanz, Fabio Efficace, Steven D Gore, Tae Kon Kim, Navel Daver, Guillermo Garcia-Manero, Maria Rozman, Alberto Orfao, Sa A Wang, M Kathryn Foucar, Ulrich Germing, Torsten Haferlach, Phillip Scheinberg, Yasushi Miyazaki, Marcelo Iastrebner, Austin Kulasekararaj, Thomas Cluzeau, Shahram Kordasti, Arjan A van de Loosdrecht, Lionel Ades, Amer M Zeidan, Matteo G Della Porta
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引用次数: 0

Abstract

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.

数据驱动的骨髓增生异常综合征统一分类系统:骨髓增生异常综合征国际联盟共识文件。
世界卫生组织和国际共识分类 2022 对骨髓增生异常综合征的分类提高了诊断的精确性,并完善了这些疾病的决策过程。然而,它们之间仍存在一些差异,可能导致在临床应用中的不一致性。我们采用了一种数据驱动的方法来协调这两种分类系统。我们研究了基因组特征的重要性及其对聚类分配过程的影响,以定义统一的实体标签。我们成立了一个由骨髓增生异常综合征国际联盟成员中的血液学专家、血液病理学专家和数据科学家组成的专家小组,并采用修改后的德尔菲共识流程来协调形态学上定义的、没有明显基因组特征的类别。专家小组定期举行在线会议,并使用在线投票工具参与了两轮调查。我们确定了九个具有明显基因组特征的群组。分层重要性最高的簇群以双拷贝 TP53 失活为特征。聚类分配与突变计数无关。单复制 TP53 失活的个体被分配到其他群组。从层次上看,第二大类包括骨髓增生异常综合征伴del(5q)。孤立的 del(5q)和骨髓中少于 5%的暴发性细胞是最相关的标签定义特征。第三大类包括SF3B1突变的骨髓增生异常综合征,不存在孤立的del(5q)、del(7q)/-7、abn3q26.2、复杂核型、RUNX1突变或双倍TP53是该类疾病统一标签的基础。从形态学角度定义的骨髓增生异常综合征实体显示出巨大的基因组异质性,而单系与多系发育不良、骨髓囊胚、细胞减少或纤维化并不能有效地反映这种异质性。我们研究了骨髓增生异常综合征(骨髓泡超过 10%)与急性髓性白血病之间的生物学连续性,发现两者的遗传特征只有部分重叠。经过调查,低血小板(即低于 5%)骨髓增生异常综合征和血小板增多(即 5%或以上)骨髓增生异常综合征被认定为疾病实体。我们的数据驱动方法可有效协调骨髓增生异常综合征的现有分类,并为现实世界中的患者管理提供参考。
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来源期刊
Lancet Haematology
Lancet Haematology HEMATOLOGY-
CiteScore
26.00
自引率
0.80%
发文量
323
期刊介绍: Launched in autumn 2014, The Lancet Haematology is part of the Lancet specialty journals, exclusively available online. This monthly journal is committed to publishing original research that not only sheds light on haematological clinical practice but also advocates for change within the field. Aligned with the Lancet journals' tradition of high-impact research, The Lancet Haematology aspires to achieve a similar standing and reputation within its discipline. It upholds the rigorous reporting standards characteristic of all Lancet titles, ensuring a consistent commitment to quality in its contributions to the field of haematology.
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