Evidence map›Paper›PMID 36299580›Full record

ArticleFrontiers in genetics2022

Endometrial cancer prognosis prediction using correlation models based on CDK family genes.

Xianhua Gu, Honghong Shen, Wenqi Bai, Zheng Xiang, Xinwei Li, Rong Zhang, Fan Shi, Huiyuan Li, Guangzheng Zhu, Suyang Guo

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 38% 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

4 citing papers in PubMed, 6 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

10 authors at 1 institution in 1 country.

Xianhua GuDepartment of Gynecological Oncology, First Affiliated Hospital of Bengbu Medical College, Bengbu, China.
Honghong ShenDepartment of Medical Oncology, First Affiliated Hospital of Bengbu Medical College, Bengbu, China.
Wenqi BaiDepartment of Gynecological Oncology, First Affiliated Hospital of Bengbu Medical College, Bengbu, China.
Zheng XiangDepartment of Surgical Oncology, First Affiliated Hospital of Bengbu Medical College, Bengbu, China.
Xinwei LiDepartment of Medical Oncology, First Affiliated Hospital of Bengbu Medical College, Bengbu, China.
Rong ZhangDepartment of Gynecological Oncology, First Affiliated Hospital of Bengbu Medical College, Bengbu, China.
Fan ShiDepartment of Pathology, First Affiliated Hospital of Bengbu Medical College, Bengbu, China.
Huiyuan LiDepartment of Medical Oncology, First Affiliated Hospital of Bengbu Medical College, Bengbu, China.
Guangzheng ZhuDepartment of Surgical Oncology, First Affiliated Hospital of Bengbu Medical College, Bengbu, China.
Suyang GuoDepartment of Gynecological Oncology, First Affiliated Hospital of Bengbu Medical College, Bengbu, China.
First Affiliated Hospital of Bengbu Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cyclin-dependent kinases (CDKs) play an important role in cell division. Given that abnormal cell proliferation caused by dysregulation of cell division is one of the major causes of endometrial cancer (EC), it is important to elucidate the role of CDK family genes in the diagnosis and prognosis of EC. In this study, The Cancer Genome Atlas (TCGA) database was used to analyze the frequency of copy number variations and somatic mutations in 26 CDK family genes. Subsequently, the expression of these genes in EC was assessed, and their relationship with overall survival (OS) was examined

Indexed as

CDK16cell cycle protein-dependent kinaseendometrial cancernomogramprognostic model

Identifiers

PMID36299580
PMCPMC9589062
OpenAlexW4304144930

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.