Evidence map›Paper›PMID 35153524›Full record

ReviewClinical Medicine Insights. Oncology2021

Cervical Carcinosarcoma: Current Understanding on Pathogenesis, Diagnosis, Management and Future Perspectives.

Xinyao Shu, Yuwen Zhou, Guixia Wei, Xiaorong Chen, Meng Qiu

Open access · goldAbstract readReview
In one paragraph

Review in Clinical Medicine Insights. Oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.3field-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

5 citing papers in PubMed, 10 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

5 authors at 1 institution in 1 country.

Xinyao ShuDepartment of Abdominal Cancer, Cancer Center, West China Hospital of Sichuan University, Chengdu, China.
Yuwen ZhouDepartment of Biotherapy, Cancer Center, West China Hospital of Sichuan University, Chengdu, China.
Guixia WeiDepartment of Abdominal Cancer, Cancer Center, West China Hospital of Sichuan University, Chengdu, China.
Xiaorong ChenDepartment of Abdominal Cancer, Cancer Center, West China Hospital of Sichuan University, Chengdu, China.
Meng QiuDepartment of Abdominal Cancer, Cancer Center, West China Hospital of Sichuan University, Chengdu, China.ORCID https://orcid.org/0000-0003-3722-6938
Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cervical carcinosarcoma (CCS) is a rare aggressive tumor which was referred to as a sarcoma initially with its morbidity less than 1% of all cervical cancers. Four theories have been proposed for the pathogenesis of CCS. The "metaplastic theory," also called "monoclonal theory," has been widely accepted so far. The most common clinical symptom of CCS is abnormal vaginal bleeding. CCS is much less common than the counterparts in uterine corpus and usually confused with uterine carcinosarcoma (UCS) or common cervical cancer. The management for CCS has been mainly extrapolated from studies of UCS or cervical cancers. However, CCS has its special anatomical position and biological behaviors and is usually diagnosed at an early stage than UCS. Currently, there is no consensus on the survival, management and prognosis factors of CCS. We reviewed and summarized the literatures regarding to the epidemiology, clinical presentations, pathogenesis, diagnosis and treatment of CCS for providing clinicians with comprehensive information to diagnose and treat this malignancy.

Indexed as

Cervical carcinosarcomaimmunohistochemistrytreatmentuterine carcinosarcoma

Identifiers

PMID35153524
PMCPMC8826264
OpenAlexW4205299196

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.