Evidence map›Paper›PMID 37064135›Full record

ArticleFrontiers in oncology2023

A novel scoring system for the quantitative prediction of prognosis in acute myeloid leukemia.

Yang Yu, Hao Wang, Jing-Jing Yang, Shu Fang, Ya-Nan Wen, Yi-Fan Jiao, Kun Qian, Ning Le, Ruo-Qi Shan, Wen-Jing Gao and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2023. 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
0.3field-weighted citation impact, top 39% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

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

12 authors at 5 institutions in 1 country.

Yang YuDepartment of Hematology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Hao WangDepartment of Hematology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
Jing-Jing YangDepartment of Hematology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
Shu FangDepartment of Hematology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
Ya-Nan WenDepartment of Hematology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
Yi-Fan JiaoDepartment of Hematology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
Kun QianDepartment of Hematology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
Ning LeDepartment of Hematology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
Ruo-Qi ShanDepartment of Hematology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
Wen-Jing GaoDepartment of Hematology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
Bao-Lai HuaDepartment of Hematology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Fei LiDepartment of Hematology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
Chinese PLA General Hospital · CNNankai University · CNPLA Academy of Military Science · CNBeijing Shijitan Hospital · CNPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Acute myeloid leukemia (AML) is a heterogeneous hematopoietic malignancy. Patient prognosis cannot be accurately assessed in National Comprehensive Cancer Network (NCCN) risk stratification subgroups based on the current criteria. This study aimed to develop a novel prognostic score model for the quantitative prediction of prognosis in AML. Results: We developed a prognostic risk scoring model of AML using differentially expressed genes to predict prognosis in patients with AML. Furthermore, we evaluated the effectiveness and clinical significance of this prognostic model in 4 AML cohorts and 905 patients with AML. A prognostic risk scoring model of AML containing eight prognosis-related genes was constructed using a multivariate Cox regression model. The model had a higher predictive value for the prognosis of AML in the training and validation sets. In addition, patients with lower scores had significantly better overall survival (OS) and even-free survival (EFS) than those with higher scores among patients with intermediate-risk AML according to the NCCN guidelines, indicating that the model could be used to further predict the prognosis of the intermediate-risk AML populations. Similarly, patients with high scores had remarkably poor OS and EFS in the normal-karyotype populations, indicating that the scoring model had an excellent predictive performance for patients with AML having normal karyotype. Conclusions: Our study provided an individualized prognostic risk score model that could predict the prognosis of patients with AML.

Indexed as

AMLprognosis predictionprognostic modelrisk scoring modelrisk stratification

Identifiers

PMID37064135
PMCPMC10098320
OpenAlexW4361270971

What OpenQuestion holds

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Read underepoch 390

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.