Evidence map›Paper›PMID 34222018›Full record

ArticleFrontiers in oncology2021

Cohort Profile: Chinese Cervical Cancer Clinical Study.

Xi-Ru Zhang, Zhi-Qiang Li, Li-Xin Sun, Ping Liu, Zhi-Hao Li, Peng-Fei Li, Hong-Wei Zhao, Bi-Liang Chen, Mei Ji, Li Wang and 4 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. 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
1.5field-weighted citation impact, top 18% 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, 13 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

14 authors at 8 institutions in 1 country.

Xi-Ru ZhangDepartment of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China.
Zhi-Qiang LiDepartment of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Li-Xin SunDepartment of Gynecologic Oncology, Shanxi Provincial Cancer Hospital, Taiyuan, China.
Ping LiuDepartment of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Zhi-Hao LiDepartment of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China.
Peng-Fei LiDepartment of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Hong-Wei ZhaoDepartment of Gynecologic Oncology, Shanxi Provincial Cancer Hospital, Taiyuan, China.
Bi-Liang ChenDepartment of Obstetrics and Gynecology, Xijing Hospital of Airforce Medical University, Xi'an, China.
Mei JiDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Li WangDepartment of Gynecologic Oncology of Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China.
Shan KangDepartment of Gynecology, The Forth Hospital of Hebei Medical University, Shijiazhuang, China.
Jing-He LangDepartment of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College, Beijing, China.
Chen MaoDepartment of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China.
Chun-Lin ChenDepartment of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Nanfang Hospital · CNSouthern Medical University · CNShanxi Provincial Cancer Hospital · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNFirst Affiliated Hospital of Zhengzhou University · CNHebei Medical University · CNXijing Hospital · CNZhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cervical cancer is the fourth most common cancer worldwide, but its incidence varies greatly in different countries. Regardless of incidence or mortality, the burden of cervical cancer in China accounts for approximately 18% of the global burden. The Chinese Cervical Cancer Clinical Study is a hospital-based multicenter open cohort. The major aims of this study include (i) to explore the associations of therapeutic strategies with complications as well as mid- and long-term clinical outcomes; (ii) to widely assess the factors which may have an influence on the prognosis of cervical cancer and then guide the treatment options, and to estimate prognosis using a prediction model for precise post-treatment care and follow-up; (iii) to develop a knowledge base of cervical clinical auxiliary diagnosis and prognosis prediction using artificial intelligence and machine learning approaches; and (iv) to roughly map the burden of cervical cancer in different districts and monitoring the trend in incidence of cervical cancer to potentially inform prevention and control strategies. Patients eligible for inclusion were those diagnosed with cervical cancer, whether during an outpatient visit or hospital admission, at 47 different types of medical institutions in 19 cities of 11 provinces across mainland China between 2004 and 2018. In a total, 63 926 patients with cervical cancer were enrolled in the cohort. Since the project inception, a large number of standardized variables have been collected, including epidemiological characteristics, cervical cancer-related symptoms, physical examination results, laboratory testing results, imaging reports, tumor biomarkers, tumor staging, tumor characteristics, comorbidities, co-infections, treatment and short-term complications. Follow-up was performed at least once every 6 months within the first 5 years after receiving treatment and then annually thereafter. At present, we are developing a cervical cancer imaging database containing Dicom files with data of computed tomography/magnetic resonance imaging examination. Additionally, we are also collecting original pathological specimens of patients with cervical cancer. Potential collaborators are welcomed to contact the corresponding authors, and anyone can submit at least one specific study proposal describing the background, objectives and methods of the study.

Indexed as

cervical cancercohortpredictionprognosistherapy

Identifiers

PMID34222018
PMCPMC8250135
OpenAlexW3176126376

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.