Evidence map›Paper›PMID 34123815›Full record

ArticleFrontiers in oncology2021

Prognostic Prediction of Cytogenetically Normal Acute Myeloid Leukemia Based on a Gene Expression Model.

Liu Yang, Houyu Zhang, Xue Yang, Ting Lu, Shihui Ma, Hui Cheng, Kuangyu Yen, Tao Cheng

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

6 citing papers in PubMed, 8 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

8 authors at 4 institutions in 1 country.

Liu YangState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
Houyu ZhangState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
Xue YangState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
Ting LuState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
Shihui MaState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
Hui ChengState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
Kuangyu YenState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
Tao ChengState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
Institute of Hematology & Blood Diseases Hospital · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNPeking Union Medical College Hospital · CNSouth China University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute myeloid leukemia (AML) refers to a heterogeneous group of hematopoietic malignancies. The well-known European Leukemia Network (ELN) stratifies AML patients into three risk groups, based primarily on the detection of cytogenetic abnormalities. However, the prognosis of cytogenetically normal AML (CN-AML), which is the largest AML subset, can be hard to define. Moreover, the clinical outcomes associated with this subgroup are diverse. In this study, using transcriptome profiles collected from CN-AML patients in the BeatAML cohort, we constructed a robust prognostic Cox model named NEST (Nine-gEne SignaTure). The validity of NEST was confirmed in four external independent cohorts. Moreover, the risk score predicted by the NEST model remained an independent prognostic factor in multivariate analyses. Further analysis revealed that the NEST model was suitable for bone marrow mononuclear cell (BMMC) samples but not peripheral blood mononuclear cell (PBMC) samples, which indirectly indicated subtle differences between BMMCs and PBMCs. Our data demonstrated the robustness and accuracy of the NEST model and implied the importance of the immune dysfunction in the leukemogenesis that occurs in CN-AML, which shed new light on the further exploration of molecular mechanisms and treatment guidance for CN-AML.

Indexed as

biomarkerbone marrowcytogenetically normal acute myeloid leukemiaimmune dysfunctionprognosis

Identifiers

PMID34123815
PMCPMC8190396
OpenAlexW3169411961

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.