Evidence map›Paper›PMID 35265226›Full record

ArticleDisease markers2022

A Novel Prognostic Four-Gene Signature of Breast Cancer Identified by Integrated Bioinformatics Analysis.

Xiaoyu Zhao, Huimin Yan, Xueqing Yan, Zhilin Chen, Rui Zhuo

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Disease markers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-weighted citation impact, top 46% 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

5 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Antiproliferative Activity ofBiomedicines · 2024
    Article
  5. Article
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

5 authors at 4 institutions in 1 country.

Xiaoyu ZhaoMedical College, Xuchang University, Xuchang, 461000, China.
Huimin YanDepartment of Pediatrics, The First Medical Center of PLA General Hospital, Beijing, 100000, China.
Xueqing YanState Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, 100000, China.
Zhilin ChenDepartment of Breast and Thoracic Oncological Surgery, The First Affiliated Hospital of Hainan Medical University, Haikou 570102, China.ORCID https://orcid.org/0000-0002-8077-6911
Rui ZhuoDepartment of Breast Surgery, Guilin TCM Hospital of China, Guilin 5410022, China.ORCID https://orcid.org/0000-0002-1262-852X
Chinese Academy of Sciences · CNChinese PLA General Hospital · CNHainan Medical University · CNXuchang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular analysis facilitates the prediction of overall survival (OS) of breast cancer and decision-making of the treatment plan. The current study was designed to identify new prognostic genes for breast cancer and construct an effective prognostic signature with integrated bioinformatics analysis. Differentially expressed genes in breast cancer samples from The Cancer Genome Atlas (TCGA) dataset were filtered by univariate Cox regression analysis. The prognostic model was optimized by the Akaike information criterion and further validated using the TCGA dataset (

Indexed as

Computational BiologyGene Expression ProfilingBreast NeoplasmsFemaleHumansMiddle AgedPrognosisSurvival Analysis

Identifiers

PMID35265226
PMCPMC8898848
OpenAlexW4214555113

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.