Evidence map›Paper›PMID 39001691›Full record

ReviewLaboratory medicine2024

TP53 mutations in myeloid neoplasms: implications for accurate laboratory detection, diagnosis, and treatment.

Linsheng Zhang, Brooj Abro, Andrew Campbell, Yi Ding

Abstract readReview
In one paragraph

Review in Laboratory medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Long-read sequencing resolvesHaematologica · 2026
    Article
  2. Article
  3. Pandora's Box of AML: HowBiomedicines · 2025
    Review
  4. Review
  5. Review
  6. Review
  7. 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

4 authors.

Linsheng ZhangDepartment of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, US.ORCID 0000-0001-5128-075X
Brooj AbroDepartment of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, US.
Andrew CampbellDepartment of Laboratory Medicine, Geisinger Medical Center, Danville, PA, US.
Yi DingDepartment of Laboratory Medicine, Geisinger Medical Center, Danville, PA, US.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic alterations that affect the function of p53 tumor suppressor have been extensively investigated in myeloid neoplasms, revealing their significant impact on disease progression, treatment response, and patient outcomes. The identification and characterization of TP53 mutations play pivotal roles in subclassifying myeloid neoplasms and guiding treatment decisions. Starting with the presentation of a typical case, this review highlights the complicated nature of genetic alterations involving TP53 and provides a comprehensive analysis of TP53 mutations and other alterations in myeloid neoplasms. Currently available methods used in clinical laboratories to identify TP53 mutations are discussed, focusing on the importance of establishing a robust testing protocol within clinical laboratories to ensure the delivery of accurate and reliable results. The treatment implications of TP53 mutations in myeloid neoplasms and clinical trial options are reviewed. Ultimately, we hope that this review provides valuable insights into the patterns of TP53 alterations in myeloid neoplasms and offers guidance to establish practical laboratory testing protocols to support the best practices of precision oncology.

Indexed as

MutationTumor Suppressor Protein p53HumansTP53 protein, humanTumor Suppressor Protein p53acute myeloid leukemiagenetic techniquesmyelodysplastic syndromemyeloid neoplasmsequence analysisTP53

Identifiers

PMID39001691
PMCPMC11532620

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.