Evidence map›Paper›PMID 34664861›Full record

ArticleMedicine2021

Construction of a 5 immune-related lncRNA-based prognostic model of NSCLC via bioinformatics.

Ya-Jie Huang, Chang-Jie Huang

Abstract read
In one paragraph

Article in Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Establishment of a Prognostic Necroptosis-Related lncRNA Signature in Ovarian Cancer.Combinatorial chemistry & high throughput screening · 2026
    Article
  2. Review
  3. Article
  4. 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

2 authors.

Ya-Jie HuangDepartment of Medical Oncology, The Fourth hospital of Hebei Medical University, Shijiazhuang, Hebei, China.ORCID 0000-0003-1533-5439
Chang-Jie HuangUndergraduate of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, China.ORCID 0000-0002-4089-0672

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

abstractParticipate in tumorigenic, oncogenic, and tumor suppressive pathways through gene expression regulation. We aimed to build an immune-related long noncoding RNA (lncRNA) prognostic model to enhance nonsmall cell lung cancer (NSCLC) prognostic prediction.The original data were collected from the cancer genome atlas database. Perl and R software were used for statistical analysis. The effects of lncRNAs expression on prognosis were analyzed by Gene Expression Profiling Interactive Analysis. Silico functional analysis were performed by DAVID Bioinformatics Resources.The median risk score as a dividing value separated patients into high- and low-risk groups. These 2 groups had different 5-year survival rates, median survival times, and immune statuses. The 5-lncRNA signature was validated as an independent prognostic factor with high accuracy (area under the receiver operating characteristic = 0.722). Silico functional analysis connected the lncRNAs with immune-related biological processes and pathways in carcinogenesis.The novel immune-related lncRNA prognostic model had significant clinical implication for enhancing lung adenocarcinoma outcome prediction and guiding the choice of treatment.

Indexed as

PrognosisArea Under CurveBibliometricsCarcinoma, Non-Small-Cell LungComputational BiologyGene Expression ProfilingGenomic LibraryHumansKaplan-Meier EstimateProportional Hazards ModelsRNA, Long NoncodingROC CurveRNA, Long Noncoding

Identifiers

PMID34664861
PMCPMC8448051

What OpenQuestion holds

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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.