Evidence map›Paper›PMID 35117549›Full record

ReviewTranslational cancer research2020

A review of the research progress in T-lymphocyte immunity and cervical cancer.

Lina Zhang, Zhilei Mao, Yiqing Lai, Ting Wan, Keliang Zhang, Beibei Zhou

Open access · diamondAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Translational cancer research, 2020. 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
1.6field-weighted citation impact, top 16% 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, 22 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Lina Zhang *Department of Cervical Diseases Treatment, Changzhou Maternity and Child Health Care Hospital Affiliated to Nanjing Medical University, Changzhou 213000, China.
Zhilei Mao *Department of Cervical Diseases Treatment, Changzhou Maternity and Child Health Care Hospital Affiliated to Nanjing Medical University, Changzhou 213000, China.
Yiqing LaiDepartment of Cervical Diseases Treatment, Changzhou Maternity and Child Health Care Hospital Affiliated to Nanjing Medical University, Changzhou 213000, China.
Ting WanDepartment of Cervical Diseases Treatment, Changzhou Maternity and Child Health Care Hospital Affiliated to Nanjing Medical University, Changzhou 213000, China.
Keliang ZhangDepartment of Cervical Diseases Treatment, Changzhou Maternity and Child Health Care Hospital Affiliated to Nanjing Medical University, Changzhou 213000, China.
Beibei ZhouDepartment of Cervical Diseases Treatment, Changzhou Maternity and Child Health Care Hospital Affiliated to Nanjing Medical University, Changzhou 213000, China.
Nanjing Maternity and Child Health Care Hospital · CNNanjing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cervical cancer develops as a result of T-cell immune evasion by human papillomavirus (HPV). T-cell immunity requires the participation of many factors, such as antigen-presenting cells (APCs), cytokines, co-stimulatory molecules, etc. HPV vaccines are promising treatments to prevent HPV infection and cervical cancer. This article mainly provides a summary of the number and function changes of T cells during HPV infection and cervical cancer development. Studies on t-cell immunotherapy, which is expected to become a new treatment for cervical cancer after surgery, radiotherapy, and chemotherapy, are also reviewed in this article.

Indexed as

cervical cancerhuman papillomavirus (HPV)immunotherapyT-cell

Identifiers

PMID35117549
PMCPMC8797462
OpenAlexW3010664388

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.