Evidence map›Paper›PMID 35938646›Full record

ArticleAmerican journal of clinical pathology2022

Abnormal CD13/HLA-DR Expression Pattern on Myeloblasts Predicts Development of Myeloid Neoplasia in Patients With Clonal Cytopenia of Undetermined Significance.

Dragan Jevremovic, Ahmad Nanaa, Susan M Geyer, Michael Timm, Haya Azouz, Cynthia Hengel, Alexander Reberg, Rong He, David Viswanatha, Mohamad E Salama and 13 more

Open access · hybridAbstract read
In one paragraph

Article in American journal of clinical pathology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 26% of its field
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

5 citing papers in PubMed, 5 citations in OpenAlex.

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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

23 authors at 3 institutions in 1 country.

Dragan JevremovicDivision of Hematopathology, Mayo Clinic, Rochester, MN, USA.ORCID 0000-0002-1792-5822
Ahmad NanaaDivision of Hematology, Mayo Clinic, Rochester, MN, USA.
Susan M GeyerDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Michael TimmDivision of Hematopathology, Mayo Clinic, Rochester, MN, USA.
Haya AzouzDivision of Hematology, Mayo Clinic, Rochester, MN, USA.
Cynthia HengelDivision of Hematopathology, Mayo Clinic, Rochester, MN, USA.
Alexander RebergDivision of Hematopathology, Mayo Clinic, Rochester, MN, USA.
Rong HeDivision of Hematopathology, Mayo Clinic, Rochester, MN, USA.ORCID 0000-0001-6116-8163
David ViswanathaDivision of Hematopathology, Mayo Clinic, Rochester, MN, USA.
Mohamad E SalamaSonic Healthcare USA, Austin, TX, USA.
Min ShiDivision of Hematopathology, Mayo Clinic, Rochester, MN, USA.ORCID 0000-0002-5741-4293
Horatiu OlteanuDivision of Hematopathology, Mayo Clinic, Rochester, MN, USA.ORCID 0000-0001-5783-4485
Pedro HornaDivision of Hematopathology, Mayo Clinic, Rochester, MN, USA.
Gregory OttesonDivision of Hematopathology, Mayo Clinic, Rochester, MN, USA.
Patricia T GreippDivision of Hematopathology, Mayo Clinic, Rochester, MN, USA.
Zhuoer XieDivision of Hematology, Mayo Clinic, Rochester, MN, USA.
Hassan B AlkhateebDivision of Hematology, Mayo Clinic, Rochester, MN, USA.
William HoganDivision of Hematology, Mayo Clinic, Rochester, MN, USA.
Mark LitzowDivision of Hematology, Mayo Clinic, Rochester, MN, USA.
Mrinal M PatnaikDivision of Hematology, Mayo Clinic, Rochester, MN, USA.
Mithun ShahDivision of Hematology, Mayo Clinic, Rochester, MN, USA.
Aref Al-KaliDivision of Hematology, Mayo Clinic, Rochester, MN, USA.
Phuong L NguyenDivision of Hematopathology, Mayo Clinic, Rochester, MN, USA.
Mayo Clinic in Arizona · USMayo Clinic · USMayo Clinic in Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesPatients with clonal cytopenia of undetermined significance (CCUS) are at increased risk of developing myeloid neoplasia (MN). We evaluated whether a simple flow cytometry immunophenotyping (FCIP) assay could differentiate the risk of development of MN in patients with CCUS.

methodsBone marrow aspirates were assessed by FCIP panel in a cohort of 80 patients identified as having CCUS based on next-generation sequencing or cytogenetics from March 2015 to May 2020, with available samples. Flow cytometric assay included CD13/HLA-DR expression pattern on CD34-positive myeloblasts; CD13/CD16 pattern on maturing granulocytic precursors; and aberrant expression of CD2, CD7, or CD56 on CD34-positive myeloblasts. Relevant demographic, comorbidity, and clinical and laboratory data, including the type and extent of genetic abnormalities, were extracted from the electronic health record.

resultsIn total, 17 (21%) patients with CCUS developed MN over the follow-up period (median survival follow-up, 28 months [95% confidence interval, 19-31]). Flow cytometry immunophenotyping abnormalities, including the aberrant pattern of CD13/HLA-DR expression, as detected at the time of the diagnosis of CCUS, were significantly associated with risk of developing MN (hazard ratio, 2.97; P = .006). Additional FCIP parameters associated with the development of MN included abnormal expression of CD7 on myeloblasts and the presence vs absence of any FCIP abnormality.

conclusionsA simple FCIP approach that includes assessment of CD13/HLA-DR pattern on CD34-positive myeloblasts can be useful in identifying patients with CCUS at higher risk of developing MN.

Indexed as

CD13 AntigensHLA-DR AntigensLeukemia, Myeloid, AcuteMyeloproliferative DisordersClonal HematopoiesisFlow CytometryGranulocyte Precursor CellsHumansImmunophenotypingLeukocyte CountCD13 AntigensHLA-DR AntigensCCUSFlow cytometryMDSMyeloid neoplasia

Identifiers

PMID35938646
PMCPMC9535519
OpenAlexW4290702076

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.