Evidence map›Paper›PMID 40234613›Full record

ReviewLeukemia2025

Prognostic scoring systems in chronic myeloid leukaemia.

Michael Lauseker, Verena S Hoffmann, Markus Pfirrmann

Abstract readReview
In one paragraph

Review in Leukemia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. [Guideline for the diagnosis and treatment of chronic myeloid leukemia in China (2025)].Zhonghua xue ye xue za zhi = Zhonghua xueyexue zazhi · 2025
    Guideline
  2. Article
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  7. Observational
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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

3 authors.

Michael LausekerInstitute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany. lauseker@ibe.med.uni-muenchen.de.ORCID 0000-0002-6662-7127
Verena S HoffmannInstitute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany.ORCID 0000-0003-1478-5390
Markus PfirrmannInstitute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany.ORCID 0000-0002-8948-0690

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prognostic scores are an important tool in medical statistics. In chronic myeloid leukaemia (CML), prognostic models have existed for many years, enabling the classification of patients into groups that can be clearly differentiated in terms of their prognosis. However, over time, the focus of these models has shifted from solely survival outcomes to a broader range of diverse endpoints. This review explores the development and applications of these scores, offering recommendations for their use, and looks ahead to potential future advancements in the field. As the landscape of CML treatment evolves with newer therapeutic options, it is crucial to adapt prognostic models to reflect not only survival rates but also other important clinical milestones such as molecular remission, progression-free survival, and CML-related survival. The continued refinement of these tools, alongside international validation efforts, will be essential in providing clinicians with more accurate and individualized patient prognostication, ultimately improving therapeutic decision-making and patient outcomes.

Indexed as

Leukemia, Myelogenous, Chronic, BCR-ABL PositiveHumansLife ExpectancyPrognosis

Identifiers

PMID40234613
PMCPMC12055577

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.