Evidence map›Paper›PMID 42100346›Full record

ArticleFrontiers in genetics2026

Charting the immune terrain: a novel risk model for thyroid cancer prognosis.

Qi Qi, Xiaoyan Cai, Qiang Lv

Abstract read
In one paragraph

Article in Frontiers in genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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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.

Qi QiDepartment of General Surgery, Shanghia Pudong New Area Gongli Hospital, Shanghai, China.
Xiaoyan CaiDepartment of General Surgery, Shanghia Pudong New Area Gongli Hospital, Shanghai, China.
Qiang LvDepartment of General Surgery, Shanghia Pudong New Area Gongli Hospital, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To construct a prognostic risk model for thyroid cancer based on immune genes and analyze the correlation between immune genes and immune infiltration. Methods: A retrospective study was conducted on 180 patients with thyroid cancer treated in our hospital during May 2022 to April 2025. Based on the prognosis, the subjects were graded as good prognosis group of 126 cases and poor prognosis group of 54 cases. The influencing factors were analyzed by a binary logistic regression model, receiver operating characteristic curve and goodness of fit test. Single sample gene set enrichment analysis was used to perform immune infiltration analysis on the expression matrix of peripheral blood mononuclear cells. The GSEA algorithm was used to calculate the abundance of tumor associated immune cell infiltration. Pearson correlation analysis was used to investigate the correlation. The TCGA-THCA database was used to analyze the differential expression of genes, as well as the correlation with clinical pathological features. Results: The expression levels of CDK1, B3GNT7, S100A9, and MMP9 genes were higher in the poor prognosis group than the good prognosis group ( Conclusion: CDK1, B3GNT7, S100A9, and MMP9 were independent risk factors for poor prognosis in thyroid cancer. The prognostic prediction model may provide objective evidence for early screening of high-risk cases in clinical practice.

Indexed as

immune genesimmune infiltrationprediction modelprognostic riskthyroid cancer

Identifiers

PMID42100346
PMCPMC13148796

What Socratic holds

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LicenceCC BY
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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 Socratic graph.