Evidence map›Paper›PMID 37258721›Full record

ArticleJournal of cancer research and clinical oncology2023

A novel 5-gene prognostic signature to improve risk stratification of cytogenetically normal acute myeloid leukemia.

Cong Deng, Tiansheng Zeng, Pei Zhu, Sijie Zhao, Zeyong Huang, Wenhui Huang, Wenjuan Zhang, Xiaojuan Huang, Lin Fu

Open access · greenAbstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 28% of its field
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

2 citing papers in PubMed, 2 citations in OpenAlex.

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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

9 authors at 1 institution in 1 country.

Cong Deng *Department of Hematology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, China.
Tiansheng Zeng *Department of Hematology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, China.
Pei ZhuDepartment of Hematology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, China.
Sijie ZhaoThe Second Clinical School of Guangzhou Medical University, Guangzhou, 511436, China.
Zeyong HuangDepartment of Hematology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, China.
Wenhui HuangDepartment of Hematology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, China.
Wenjuan ZhangDepartment of Hematology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, China.
Xiaojuan HuangDepartment of Hematology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, China.
Lin FuDepartment of Hematology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510260, China. fulin022@126.com.
Second Affiliated Hospital of Guangzhou Medical University · CN

Funding

National Natural Science Foundation of China 81500118National Natural Science Foundation of China-Xinjiang Joint Fund U1903117
6 · The paper itself

Abstract

purposePrognostic prediction is a challenging task in cytogenetically normal acute myeloid leukemia (CN-AML) patients. In this study, we aimed at developing a novel prognostic signature to predict and stratify the survival of CN-AML patients.

methodsUsing a training dataset (GSE12417), 5-gene prognostic signature was established to predict survival of CN-AML patients. The prognostic performance of this prognostic signature was further validated in testing dataset (TCGA CN-AML cohort) and validation dataset (GSE6891 CN-AML cohort).

resultsIn training, testing and validation datasets, the increased 5-gene risk score was significantly related with inferior overall survival (OS) of patients, and the area under the receiver operating characteristic curve (AUC) demonstrated that our prognostic signature had overall prediction accuracy. The excellent prognostic value of the 5-gene prognostic signature was also supported by the comparison with three previously proposed prognostic models. For the intermediate-risk CN-AML patients and the CN-AML patients with FLT3 or NPM1 mutation, our model could also well dichotomize them into two subgroups with distinct prognosis. Multivariate analysis demonstrated that 5-gene risk score was the only independent risk factor in TCGA CN-AML cohort. Nomogram including the 5-gene risk score performed well in predicting 1-year, 2-year and 3-year OS.

conclusionIn summary, our novel 5-gene prognostic signature facilitated the improvement in risk stratification of CN-AML patients.

Indexed as

Leukemia, Myeloid, AcuteHumansMutationNomogramsPrognosisRisk AssessmentRisk FactorsCytogenetically normal acute myeloid leukemiaGene expression profilingPrognostic signatureRisk stratification

Identifiers

PMID37258721
PMCPMC11796839
OpenAlexW4378800559

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.