Evidence map›Paper›PMID 32952743›Full record

ArticleDisease markers2020

Identification of Key Genes of Prognostic Value in Clear Cell Renal Cell Carcinoma Microenvironment and a Risk Score Prognostic Model.

Enfa Zhao, Xiaofang Bai

Abstract read
In one paragraph

Article in Disease markers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. 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

2 authors.

Enfa ZhaoDepartment of Structural Heart Disease, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China.ORCID https://orcid.org/0000-0002-8028-2997
Xiaofang BaiDepartment of Ultrasound Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China.ORCID https://orcid.org/0000-0002-8799-1809

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveWe aimed at identifying the key genes of prognostic value in clear cell renal cell carcinoma (ccRCC) microenvironment and construct a risk score prognostic model. MATERIALS AND

methodsImmune and stromal scores were calculated using the ESTIMATE algorithm. A total of 539 ccRCC cases were divided into high- and low-score groups. The differentially expressed genes in immune and stromal cells for the prognosis of ccRCC were screened. The relationship between survival outcome and gene expression was evaluated using univariate and multivariate Cox proportional hazard regression analyses. A risk score prognostic model was constructed based on the immune/stromal scores.

resultsThe median survival time of the low immune score group was longer than that of the high immune score group (

conclusionsLow immune scores were associated with extended survival time compared to high immune scores. The novel risk predictive model based on tumor microenvironment-related genes may be an independent prognostic biomarker in ccRCC.

Indexed as

Gene Regulatory NetworksAgedBiomarkers, TumorCarcinoma, Renal CellFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKidney NeoplasmsMaleMiddle AgedModels, TheoreticalNeoplasm StagingOligonucleotide Array Sequence AnalysisPrognosisSurvival AnalysisBiomarkers, Tumor

Identifiers

PMID32952743
PMCPMC7487089

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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.