Diagnostic algorithm for lower-risk myelodysplastic syndromes

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

*Corresponding author for this work

    Research output: Contribution to journalReview articlepeer-review

    10 Citations (Scopus)
    289 Downloads (Pure)

    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.

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

    Fingerprint

    Dive into the research topics of 'Diagnostic algorithm for lower-risk myelodysplastic syndromes'. Together they form a unique fingerprint.

    Cite this