Evidence map›Paper›PMID 39352624›Full record

ReviewInternational journal of hematology2024

Recent progress in AML with recurrent genetic abnormalities.

Yuichi Ishikawa

Abstract readReview
PubMed Publisher
In one paragraph

Review in International journal of hematology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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

1 author.

Yuichi IshikawaDepartment of Hematology and Oncology, Nagoya University Graduate School of Medicine, 65 Tsurumai-Cho, Showa-ku, Nagoya, 466-8550, Japan. yishikaw@med.nagoya-u.ac.jp.ORCID http://orcid.org/0000-0001-6024-6617

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute myeloid leukemia (AML) is a heterogeneous disease characterized by various molecular abnormalities that significantly impact its pathogenesis and prognosis. Currently, the prognosis of AML patients is stratified on the basis of co-existing chromosomal and genetic abnormalities. AML patients with NPM1 or CEBPA mutations, which are frequently identified in cytogenetically normal AML, are classified in the favorable-risk group, although approximately 40% of patients relapse. Similarly, a clinical high-risk group has been identified among patients with acute promyelocytic leukemia, but the underlying molecular abnormalities remain unclear. FLT3 mutations frequently overlap in these favorable-risk AMLs, including core binding factor AML, and their prognostic impact is still controversial. As such, further risk stratification and treatment optimization based on various molecular abnormalities are warranted to improve the prognosis of favorable-risk AMLs. These molecular abnormalities are also considered therapeutic targets, and targeted therapies have been developed over the years. In recent years, several targeted agents have been approved and demonstrated to improve the prognosis of AML. However, resistance to targeted therapies is also a challenge. This Progress in Hematology features current trends and challenges in favorable-risk AML and FLT3 mutations that are frequently identified in these patients.

Indexed as

fms-Like Tyrosine Kinase 3Leukemia, Myeloid, AcuteMutationNucleophosminCCAAT-Enhancer-Binding ProteinsHumansMolecular Targeted TherapyNuclear ProteinsPrognosisCCAAT-Enhancer-Binding ProteinsCEBPA protein, humanFLT3 protein, humanfms-Like Tyrosine Kinase 3NPM1 protein, humanNuclear ProteinsNucleophosminAMLFavorable riskFLT3 mutationMolecular targeted therapyRecurrent genetic abnormalities

Identifiers

What OpenQuestion holds

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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.