Evidence map›Paper›PMID 32782559›Full record

ArticleOncology letters2020

An optimal prognostic model based on gene expression for clear cell renal cell carcinoma.

Dan Xu, Wantai Dang, Shaoqing Wang, Bo Hu, Lianghong Yin, Baozhang Guan

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

Article in Oncology letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.6field-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

7 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

6 authors at 2 institutions in 1 country.

Dan XuDepartment of Nephrology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, P.R. China.
Wantai DangDepartment of Rheumatology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan 610500, P.R. China.
Shaoqing WangDepartment of Nephrology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan 610500, P.R. China.
Bo HuDepartment of Nephrology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, P.R. China.
Lianghong YinDepartment of Nephrology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, P.R. China.
Baozhang GuanDepartment of Nephrology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, P.R. China.
First Affiliated Hospital of Jinan University · CNFirst Affiliated Hospital of Chengdu Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of RCC; however, prognostic prediction tools for ccRCC are scant. Developing mRNA or long non-coding RNA (lncRNA)-based risk assessment tools may improve the prognosis in patients with ccRCC. RNA-sequencing and prognostic data from patients with ccRCC were downloaded from The Cancer Genome Atlas and the European Bioinformatics Institute Array database at the

Indexed as

DEGslncRNAspathway enrichment analysisprognostic modelrisk score

Identifiers

PMID32782559
PMCPMC7400162
OpenAlexW3037878983

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.