Evidence map›Paper›PMID 30643174›Full record

ArticleScientific reports2019

Astrocytoma progression scoring system based on the WHO 2016 criteria.

Zhen-Hang Li, Yan-Lei Guan, Qiang Liu, Yao Wang, Run Cui, Yun-Jie Wang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

13 citing papers in PubMed, 17 citations in OpenAlex.

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  9. TheExperimental biology and medicine (Maywood, N.J.) · 2020
    Review
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  11. Open Data for Differential Network Analysis in Glioma.International journal of molecular sciences · 2020
    Article
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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

6 authors at 2 institutions in 1 country.

Zhen-Hang LiDepartment of Neurosurgery, The First Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning Province, 110001, PR China.
Yan-Lei GuanDepartment of Neurosurgery, The First Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning Province, 110001, PR China.
Qiang LiuDepartment of Neurosurgery, The First Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning Province, 110001, PR China.
Yao WangDepartment of Neurosurgery, The First Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning Province, 110001, PR China.
Run CuiDepartment of Neurosurgery, The First Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning Province, 110001, PR China.
Yun-Jie WangDepartment of Neurosurgery, The First Hospital of China Medical University, No. 155, Nanjing North Street, Heping District, Shenyang, Liaoning Province, 110001, PR China. Dryunjiewang@hotmail.com.
China Medical University · CNFirst Hospital of China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diffuse astrocytoma (including glioblastoma) is morbid with a worse prognosis than other types of glioma. Therefore, we sought to build a progression-associated score to improve malignancy and prognostic predictions for astrocytoma. The astrocytoma progression (AP) score was constructed through bioinformatics analyses of the training cohort (TCGA RNA-seq) and included 18 genes representing distinct aspects of regulation during astrocytoma progression. This classifier could successfully discriminate patients with distinct prognoses in the training and validation (REMBRANDT, GSE16011 and TCGA-GBM Microarray) cohorts (P < 0.05 in all cohorts) and in different clinicopathological subgroups. Distinct patterns of somatic mutations and copy number variation were also observed. The bioinformatics analyses suggested that genes associated with a higher AP score were significantly involved in cancer progression-related biological processes, such as the cell cycle and immune/inflammatory responses, whereas genes associated with a lower AP score were associated with relatively normal nervous system biological processes. The analyses indicated that the AP score was a robust predictor of patient survival, and its ability to predict astrocytoma malignancy was well elucidated. Therefore, this bioinformatics-based scoring system suggested that astrocytoma progression could distinguish patients with different underlying biological processes and clinical outcomes, facilitate more precise tumour grading and possibly shed light on future classification strategies and therapeutics for astrocytoma patients.

Indexed as

AdultAgedAged, 80 and overAstrocytomaComputational BiologyFemaleHumansMachine LearningMaleMicroarray AnalysisMiddle AgedNeoplasm GradingPathology, MolecularPrognosisSurvival AnalysisYoung Adult

Identifiers

PMID30643174
PMCPMC6331604
OpenAlexW2909505816

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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.