Evidence map›Paper›PMID 38737702›Full record

ArticleTranslational cancer research2024

Identification of immune-related prognostic biomarkers in triple-negative breast cancer.

Xiao-Qing Song, Zhi-Ming Shao

Abstract read
In one paragraph

Article in Translational cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

2 authors.

Xiao-Qing SongKey Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
Zhi-Ming ShaoKey Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Triple-negative breast cancer (TNBC), a type of breast cancer, lacks immune-related markers that can be used for prognosis or prediction. Therefore, we created a predictive framework for TNBC using a risk assessment. Methods: Our previous study group consisted of 360 individuals who were diagnosed with TNBC through pathology using RNA sequencing and had clinical data from Fudan University Shanghai Cancer Center (FUSCC). A risk scoring model was constructed using the Cox regression method with the least absolute shrinkage and selection operator (LASSO). A multivariate Cox regression analysis was utilized to develop the prediction model, which was then assessed using the consistency index and calibration plots. The validation cohort of The Cancer Genome Atlas (TCGA) TNBC confirmed the strength of the signatures' predictive value. Results: The prognostic risk score model included 12 genes: Conclusions: In conclusion, the prognostic signature consisting of 12 genes can assist in the choice of immunotherapy for TNBC.

Indexed as

biomarkerimmune risk scoreprognosisTriple-negative breast cancer (TNBC)

Identifiers

PMID38737702
PMCPMC11082668

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.