Evidence map›Paper›PMID 38428404›Full record

ArticleAging2024

A novel classification predicts prognosis and drug sensitivity in osteosarcoma based on alterations in gene sets.

Shuxi Ye, Xiaopeng Wang, Rongchun Chen

Open access · hybridAbstract read
In one paragraph

Article in Aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

3 authors at 1 institution in 1 country.

Shuxi YeDepartment of Spine Surgery, Ganzhou People’s Hospital, Ganzhou, Jiangxi, China.
Xiaopeng WangDepartment of Spine Surgery, Ganzhou People’s Hospital, Ganzhou, Jiangxi, China.
Rongchun ChenDepartment of Spine Surgery, Ganzhou People’s Hospital, Ganzhou, Jiangxi, China.
Ganzhou People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osteosarcoma is a cancer originating in the bone cells, specifically in the osteoblasts. Previous studies mainly focused on particular molecules but the whole pathway network. We comprehensively analyzed the enrichment score of each signal pathway and identified a novel classification by 20 machine learning algorithms. Furthermore, differences in tumor immune infiltration cells and drug sensitivity were compared in low and high groups. We identified a model consisting of four signaling pathways that predict the prognosis and the immune status of the tumor microenvironment and drug sensitivity in osteosarcoma patients. The novel classification may be used in clinical applications to predict prognosis and drug sensitivity.

Indexed as

Bone NeoplasmsOsteosarcomaAlgorithmsHumansOsteoblastsPrognosisTumor Microenvironmentdrug sensitivityosteosarcomapathwaystumor microenvironment

Identifiers

PMID38428404
PMCPMC10968677
OpenAlexW4392241644

What Socratic 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 Socratic graph.