Evidence map›Paper›PMID 41987904›Full record

ArticleHemaSphere2026

Machine learning enhances risk stratification and treatment failure prediction in diffuse large B-cell lymphoma.

Mikkel Werling, Alexander D Fuglkjær, Peter Brown, Carsten U Niemann, Rudi Agius

Abstract read
In one paragraph

Article in HemaSphere, 2026. 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

5 authors.

Mikkel WerlingDepartment of Hematology Copenhagen University Hospital-Rigshospitalet Copenhagen Denmark.ORCID https://orcid.org/0009-0008-0116-2729
Alexander D FuglkjærDepartment of Materials and Production Aalborg University Aalborg Denmark.ORCID https://orcid.org/0009-0000-3879-1950
Peter BrownDepartment of Hematology Copenhagen University Hospital-Rigshospitalet Copenhagen Denmark.ORCID https://orcid.org/0000-0002-6522-4086
Carsten U NiemannDepartment of Hematology Copenhagen University Hospital-Rigshospitalet Copenhagen Denmark.ORCID https://orcid.org/0000-0001-9880-5242
Rudi AgiusDepartment of Hematology Copenhagen University Hospital-Rigshospitalet Copenhagen Denmark.ORCID https://orcid.org/0009-0008-1444-8953

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma subtype worldwide. Existing prognostic models, including the National Comprehensive Cancer Network International Prognostic Index (NCCN IPI), rely on small predefined variable sets, discretized inputs, and do not incorporate longitudinal clinical histories or nonlinear relationships. To address these limitations, we present

Identifiers

PMID41987904
PMCPMC13077786

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.