Evidence map›Paper›PMID 37809743›Full record

ArticleHeliyon2023

Prognostic and immunological characterization of diffuse large B-cell lymphoma evaluated by co-stimulatory molecular-related features.

Lixia Sheng, Tongyu Li, Yun Li, Miao Zhou, Jiaping Wang, Yanli Lai, Yanli Zhang, Ping Yi, Qitian Mu, Guifang Ouyang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.8field-weighted citation impact, top 7% 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

14 citing papers in PubMed, 15 citations in OpenAlex.

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  13. DLD is a potential therapeutic target for COVID-19 infection in diffuse large B-cell lymphoma patients.Apoptosis : an international journal on programmed cell death · 2024
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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

10 authors at 1 institution in 1 country.

Lixia ShengDepartment of Hematology, Pital of Ningbo University, No.59 Liuting Street, Ningbo, Zhejiang, People's Republic of China.
Tongyu LiDepartment of Hematology, Pital of Ningbo University, No.59 Liuting Street, Ningbo, Zhejiang, People's Republic of China.
Yun LiKindstar Global Precision Medicine Institute, Wuhan, China.
Miao ZhouDepartment of Hematology, Pital of Ningbo University, No.59 Liuting Street, Ningbo, Zhejiang, People's Republic of China.
Jiaping WangDepartment of Hematology, Pital of Ningbo University, No.59 Liuting Street, Ningbo, Zhejiang, People's Republic of China.
Yanli LaiDepartment of Hematology, Pital of Ningbo University, No.59 Liuting Street, Ningbo, Zhejiang, People's Republic of China.
Yanli ZhangDepartment of Hematology, Pital of Ningbo University, No.59 Liuting Street, Ningbo, Zhejiang, People's Republic of China.
Ping YiKindstar Global Precision Medicine Institute, Wuhan, China.
Qitian MuDepartment of Hematology, Pital of Ningbo University, No.59 Liuting Street, Ningbo, Zhejiang, People's Republic of China.
Guifang OuyangDepartment of Hematology, Pital of Ningbo University, No.59 Liuting Street, Ningbo, Zhejiang, People's Republic of China.
Ningbo University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Co-stimulatory molecules have been shown to enhance antitumor immune responses, but their role in Diffuse Large B-cell Lymphoma (DLBCL) remains unexplored. Methods: This study aimed to explore the molecular typing of DLBCL with co-stimulatory molecule genes and to construct a prognostic profile to improve treatment decisions and clinical outcomes. Results: We conducted the first comprehensive analysis of co-stimulatory molecules in DLBCL patients and identified five co-stimulatory molecule genes with prognostic and diagnostic values. Consensus cluster analysis based on these five co-stimulatory molecule genes revealed that the two identified clusters had different distribution patterns and prognostic differences. Co-stimulatory molecular correlation signatures were then constructed based on these five co-stimulatory molecular genes and validated in an external dataset, showing good performance in predicting patient prognosis. The signature is an independent risk factor for DLBCL patients and significantly correlates with clinical factors in patients and can be used as a complement to clinical factors. Furthermore, the signature was associated with the tumor immune microenvironment. Patients identified as being at high risk according to our signature exhibit high levels of immune cell infiltration microenvironment. Conclusions: In conclusion, our signature can provide clinicians with prognostic predictions and help guide the treatment of patients with DLBCL.

Indexed as

Co-stimulatory moleculeDiffuse large B-Cell lymphomaImmune microenvironmentInfiltrationPrognosis

Identifiers

PMID37809743
PMCPMC10558338
OpenAlexW4386278209

What OpenQuestion holds

Textmetadata
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.