Evidence map›Paper›PMID 40291070›Full record

ArticleEJHaem2025

Enhanced Disease Detection of Hairy Cell Leukaemia Through Next-Generation Sequencing Based

Simon Wu, Tamia Nguyen, Imogen Caldwell, Sally Hunter, Sushmitha Kannan, Camille Santos, Yan Zhuang Yap, Clarissa Wilson, Mayani Rawicki, Constantine S Tam and 3 more

Abstract read
In one paragraph

Article in EJHaem, 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

13 authors.

Simon WuDepartment of Pathology Peter MacCallum Cancer Centre Melbourne Victoria Australia.ORCID https://orcid.org/0000-0002-8339-7343
Tamia NguyenDepartment of Pathology Peter MacCallum Cancer Centre Melbourne Victoria Australia.
Imogen CaldwellDepartment of Pathology Peter MacCallum Cancer Centre Melbourne Victoria Australia.
Sally HunterDepartment of Pathology Peter MacCallum Cancer Centre Melbourne Victoria Australia.
Sushmitha KannanDepartment of Pathology Peter MacCallum Cancer Centre Melbourne Victoria Australia.
Camille SantosDepartment of Pathology Peter MacCallum Cancer Centre Melbourne Victoria Australia.
Yan Zhuang YapDepartment of Pathology Peter MacCallum Cancer Centre Melbourne Victoria Australia.
Clarissa WilsonDepartment of Pathology Peter MacCallum Cancer Centre Melbourne Victoria Australia.
Mayani RawickiDepartment of Medicine Faculty of Medicine Dentistry and Health Sciences The University of Melbourne Melbourne Victoria Australia.
Constantine S TamDepartment of Haematology The Alfred Hospital Melbourne Victoria Australia.ORCID https://orcid.org/0000-0002-9759-5017
Rachel KoldejDepartment of Medicine Faculty of Medicine Dentistry and Health Sciences The University of Melbourne Melbourne Victoria Australia.
David RitchieSir Peter MacCallum Department of Oncology The University of Melbourne Melbourne Victoria Australia.
Piers BlomberyDepartment of Pathology Peter MacCallum Cancer Centre Melbourne Victoria Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Longitudinal disease assessment by molecular techniques is not routine in hairy cell leukaemia (HCL). Combining Results: Conclusion: Through multiple patient-specific genomic targets to improve sensitivity, NGS may potentially improve disease detection in HCL. Trial Registration: The authors have confirmed clinical trial registration is not needed for this submission.

Indexed as

geneshairy cell leukaemiaimmunoglobulin geneslymphomasmolecularNHL

Identifiers

PMID40291070
PMCPMC12032534

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.