Evidence map›Paper›PMID 35845286›Full record

ArticleEJHaem2021

An open-source, expert-designed decision tree application to support accurate diagnosis of myeloid malignancies.

Thomas Coats, Daniel Bean, Theodora Vatopoulou, Dhanapal Vijayavalli, Razan El-Bashir, Aikaterini Panopoulou, Henry Wood, Manujasri Wimalachandra, Jason Coppell, Patrick Medd and 6 more

Abstract read
In one paragraph

Article in EJHaem, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

16 authors.

Thomas CoatsDepartment of Haematology Royal Devon and Exeter NHS Foundation Trust Exeter UK.ORCID https://orcid.org/0000-0003-4341-4361
Daniel BeanBiostatistics and Health Informatics King's College London London UK.
Theodora VatopoulouDepartment of Haematology St George's University Hospitals NHS Foundation Trust London UK.
Dhanapal VijayavalliDepartment of Haematology Medway NHS Foundation Trust Kent UK.
Razan El-BashirDepartment of Haematology Medway NHS Foundation Trust Kent UK.
Aikaterini PanopoulouDepartment of Haematology Darent Valley Hospital Kent UK.
Henry WoodDepartment of Haematological Medicine King's College Hospital NHS Foundation Trust London UK.ORCID https://orcid.org/0000-0002-3503-5399
Manujasri WimalachandraDepartment of Haematological Medicine King's College Hospital NHS Foundation Trust London UK.
Jason CoppellDepartment of Haematology Royal Devon and Exeter NHS Foundation Trust Exeter UK.
Patrick MeddDepartment of Haematology Derriford Hospital Plymouth UK.
Michelle FurtadoDepartment of Haematology Royal Cornwall NHS Trust Truro UK.
David TuckerDepartment of Haematology Royal Cornwall NHS Trust Truro UK.ORCID https://orcid.org/0000-0002-0481-4111
Austin KulasakerarajDepartment of Haematological Medicine King's College Hospital NHS Foundation Trust London UK.
Joya PawadeDepartment of Pathology North Bristol NHS Trust Bristol UK.
Richard DobsonBiostatistics and Health Informatics King's College London London UK.
Robin IrelandDepartment of Haematological Medicine King's College Hospital NHS Foundation Trust London UK.

Funding

Medical Research Council MC_PC_17214Medical Research Council MR/S00310X/1
6 · The paper itself

Abstract

Accurate, reproducible diagnoses can be difficult to make in haemato-oncology due to multi-parameter clinical data, complex diagnostic criteria and time-pressured environments. We have designed a decision tree application (DTA) that reflects WHO diagnostic criteria to support accurate diagnoses of myeloid malignancies. The DTA returned the correct diagnoses in 94% of clinical cases tested. The DTA maintained a high level of accuracy in a second validation using artificially generated clinical cases. Optimisations have been made to the DTA based on the validations, and the revised version is now publicly available for use at http://bit.do/ADAtool.

Indexed as

classificationsclinical haematologydiagnostic haematologymyeloid leukaemia

Identifiers

PMID35845286
PMCPMC9175663

What OpenQuestion holds

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LicenceCC BY
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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.