Evidence map›Paper›PMID 41163355›Full record

ArticleCell cycle (Georgetown, Tex.)

Integration of a 4-gene risk score model enhances prognostic accuracy in acute myeloid leukemia.

Yiqing Li, Boqi Li, Jie Xiao, Kezhi Huang, Yuchan Liang, Peiting Zeng, Wenjuan Yang, Danian Nie

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell cycle (Georgetown, Tex.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Yiqing LiDepartment of Hematology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Boqi LiDepartment of Hematology, the Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, China.ORCID 0000-0002-6844-8579
Jie XiaoDepartment of Hematology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Kezhi HuangDepartment of Hematology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Yuchan LiangDepartment of Hematology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Peiting ZengDepartment of Hematology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Wenjuan YangDepartment of Hematology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Danian NieDepartment of Hematology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.ORCID 0000-0001-6007-6582

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The clinical outcomes of acute myeloid leukemia (AML) patients exhibit substantial heterogeneity, with relapse posing a formidable challenge. Herein, we developed a risk score model by integrating relapse-related genes through Cox regression analysis. The relapse-related genes were identified via differential gene expression analysis of 15 matched diagnosed and relapsed AML samples retrieved from the Gene Expression Omnibus (GEO) database. These genes include

Indexed as

Leukemia, Myeloid, AcuteCore Binding Factor Alpha 2 SubunitFemalefms-Like Tyrosine Kinase 3Gene Expression Regulation, LeukemicHumansMaleMiddle AgedMutationNucleophosminPrognosisRisk FactorsCore Binding Factor Alpha 2 SubunitFLT3 protein, humanfms-Like Tyrosine Kinase 3NPM1 protein, humanNucleophosminRUNX1 protein, humanAcute myeloid leukemiabioinformaticsEuropean LeukemiaNetrelapserisk score

Identifiers

PMID41163355
PMCPMC12710893

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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.