Evidence map›Paper›PMID 35386212›Full record

ArticleJournal of oncology2022

A Risk-Scoring Model Based on Evaluation of Ferroptosis-Related Genes in Osteosarcoma.

Mingyang Jiang, Zifan Wang, Xiaoyu He, Yang Hu, Mingjing Xie, Yiji Jike, Zhandong Bo, Wentao Qin

Open access · hybridAbstract read
In one paragraph

Article in Journal of oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

12 citing papers in PubMed, 15 citations in OpenAlex.

  1. [The role and mechanism of chemokine network in promoting osteoarthritis progression by regulating synovial macrophage heterogeneity].Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2026
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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

8 authors at 3 institutions in 1 country.

Mingyang Jiang *Department of Bone and Joint Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.ORCID https://orcid.org/0000-0002-3277-9536
Zifan Wang *Department of Burn Plastic and Wound Repair, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise 533000, China.
Xiaoyu He *Department of Thoracic Surgery, The Shenzhen Bao'an District Songgang People's Hospital, Shenzhen, China.
Yang HuDepartment of Bone and Joint Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
Mingjing XieDepartment of Bone and Joint Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
Yiji JikeDepartment of Bone and Joint Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
Zhandong BoDepartment of Bone and Joint Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
Wentao QinDepartment of Bone and Joint Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.ORCID https://orcid.org/0000-0003-2210-8701
Guangxi Medical University · CNAffiliated Hospital of Youjiang Medical University for Nationalities · CNShenzhen Bao'an District People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Osteosarcoma (OS) is a bone malignancy frequently seen in pediatrics and has high mortality and incidence. Ferroptosis is an important cell death process in regulating the apoptosis and invasion of tumor cells, so constructing the risk-scoring model based on OS ferroptosis-related genes (FRGs) will benefit the evaluation of both treatment and prognosis. Methods: The OS dataset was screened from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, and OS-related FRGs were found through the Ferroptosis Database (FerrDb) using a multivariate Cox regression model, followed by the generation of the risk scores and a risk-scoring prediction model. Further systematical exploration for immune cell infiltration and assessing the prediction of response to targeted drugs was conducted. Results: Based on OS-related FRGs, a risk-scoring model of FRGs in OS was constructed. The six FRGs played a role in the carbon metabolism, glutathione metabolism, and pentose phosphate pathways. Results from targeted drug sensitivity analyses were concordant to pathway analyses. The response to targeted drugs statistically differed between the two groups with different risks, and the high-risk group presented a high sensitivity to targeted drugs. Conclusions: We identified a 6-ferroptosis-gene-based prognostic signature in OS and created and verified a risk-scoring model to predict the prognosis of OS at 1, 3, and 5 years for OS patients independently.

Identifiers

PMID35386212
PMCPMC8979715
OpenAlexW4220872236

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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.