Evidence map›Paper›PMID 39428913›Full record

ReviewHistopathology2025

Can molecular patterns help to classify overlapping entities in myeloid neoplasms?

Gregor Hoermann, Joseph D Khoury

Abstract readReview
In one paragraph

Review in Histopathology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Gregor HoermannMLL Munich Leukemia Laboratory, Munich, Germany.ORCID https://orcid.org/0000-0002-7374-4380
Joseph D KhouryDepartment of Pathology, Microbiology, and Immunology, University of Nebraska Medical Center, Omaha, USA.ORCID https://orcid.org/0000-0003-2621-3584

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Myeloid neoplasms include myeloproliferative and myelodysplastic neoplasms and acute myeloid leukaemia. Historically, these diseases have been diagnosed based on clinicopathological features with sometimes arbitrary thresholds that have persisted even as molecular features were gradually incorporated into their classification. As such, although current diagnostic approaches can classify the majority of myeloid neoplasms accurately using a combination of molecular and clinicopathological features, some areas of overlap persist and occasionally pose diagnostic challenges. These include overlap across BCR::ABL1-negative myeloproliferative neoplasms; between clonal cytopenia of undetermined significance and myelodysplastic neoplasms; myelodysplastic/myeloproliferative neoplasms; and, detection of KIT mutations in myeloid neoplasms other than mastocytosis, raising the prospect of systemic mastocytosis. Molecular testing has become state of the art in the diagnostic work-up of myeloid neoplasms, and molecular patterns can inherently help to classify overlapping entities if considered within a framework of haematological presentations. For future development, molecular testing will likely include whole genome and transcriptome sequencing, and primarily molecular classifications of myeloid neoplasms have already been suggested. As such, genetically defined groups should still constitute the basis for our understanding of disease development from early onset to progression, while clinicopathological features could then be used to describe the stage of the disease rather than the specific type of myeloid neoplasm.

Indexed as

Myeloproliferative DisordersHumansLeukemia, Myeloid, AcuteMutationMyelodysplastic Syndromeschronic myelomonocytic leukaemiadisease classificationgeneticsmolecular patternsmyelodysplastic neoplasmsmyeloid neoplasmsmyeloproliferative neoplasmssystemic mastocytosis

Identifiers

PMID39428913
PMCPMC11648353

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