Evidence map›Paper›PMID 37868302›Full record

ArticleBiochemistry and biophysics reports2023

A novel immune-related prognostic model with surgical status to predict tumor immune cell infiltration and drug sensitivity in head and neck squamous cell carcinoma.

Lang Wang, Xianchao Yu, Hongwei Li, Chenglong Wang

Open access · goldAbstract read
In one paragraph

Article in Biochemistry and biophysics reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 53% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 2 institutions in 1 country.

Lang WangDepartment of Radiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan Province, 610041, PR China.
Xianchao YuSchool of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan Province, 611731, PR China.
Hongwei LiDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, Sichuan Province, 621000, PR China.
Chenglong WangDepartment of Radiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan Province, 610041, PR China.
Sichuan University · CNUniversity of Electronic Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumor-infiltrating immune cells (TICs) affect tumorigenesis and tumor development in head and neck squamous cell carcinoma (HNSCC). We constructed a novel predictive model for HNSCC based on immune-related genes (IRGs) from The Cancer Genome Atlas and the Immunology Database and Analysis Portal. After identifying the IRGs, a predictive model involving 13 IRGs with high stratification value of overall survival (OS) was constructed by multiple support vector machine recursive feature elimination and least absolute shrinkage and selection operator regression. We explored the relationship between the risk score (RS) and clinical characteristics. The nomogram showed high concordance and good agreement in OS. Four TICs affected the OS and were in agreement with the abundance analysis of the RS levels. Furthermore, the low-risk HNSCC group showed higher expression of PD-1, CTLA4, and TIGIT, while the high-risk group showed higher expression of EGFR. The high-risk HNSCC showed high sensitivity to eight drugs.

Indexed as

Drug sensitivityHNSCCPrognostic modelTumor-infiltrating immune cell

Identifiers

PMID37868302
PMCPMC10585349
OpenAlexW4387647428

What OpenQuestion holds

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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.