King's College London

Research portal

Diagnostic algorithm for lower-risk myelodysplastic syndromes

Research output: Contribution to journalReview article

Ghulam J. Mufti, Donal P. McLornan, Arjan A. van de Loosdrecht, Ulrich Germing, Robert P. Hasserjian

Original languageEnglish
Pages (from-to)1679-1696
Number of pages18
JournalLeukemia
Volume32
Issue number8
DOIs
Publication statusPublished - 1 Aug 2018

Documents

King's Authors

Abstract

Rapid advances over the past decade have uncovered the heterogeneous genomic and immunologic landscape of myelodysplastic syndromes (MDS). This has led to notable improvements in the accuracy and timing of diagnosis and prognostication of MDS, as well as the identification of possible novel targets for therapeutic intervention. For the practicing clinician, however, this increase in genomic, epigenomic, and immunologic knowledge needs consideration in a “real-world” context to aid diagnostic specificity. Although the 2016 revision to the World Health Organization classification for MDS is comprehensive and timely, certain limitations still exist for day-to-day clinical practice. In this review, we describe an up-to-date diagnostic approach to patients with suspected lower-risk MDS, including hypoplastic MDS, and demonstrate the requirement for an “integrated” diagnostic approach. Moreover, in the era of rapid access to massive parallel sequencing platforms for mutational screening, we suggest which patients should undergo such analyses, when such screening should be performed, and how those data should be interpreted. This is particularly relevant given the recent findings describing age-related clonal hematopoiesis.

Download statistics

No data available

View graph of relations

© 2018 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454