Evidence map›Paper›PMID 33194734›Full record

ArticleFrontiers in oncology2020

DCE-MRI Quantitative Parameters as Predictors of Treatment Response in Patients With Locally Advanced Cervical Squamous Cell Carcinoma Underwent CCRT.

Bing Liu, Zhen Sun, Wan-Ling Ma, Jing Ren, Guang-Wen Zhang, Meng-Qi Wei, Wei-Huan Hou, Bing-Xin Hou, Li-Chun Wei, Yi Huan and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.2field-weighted citation impact, top 17% 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

11 citing papers in PubMed, 20 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

11 authors at 3 institutions in 1 country.

Bing LiuDepartment of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Zhen SunDepartment of Orthopedic, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Wan-Ling MaDepartment of Radiology, Longgang District People's Hospital, Shenzhen, China.
Jing RenDepartment of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Guang-Wen ZhangDepartment of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Meng-Qi WeiDepartment of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Wei-Huan HouDepartment of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Bing-Xin HouDepartment of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Li-Chun WeiDepartment of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Yi HuanDepartment of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Min-Wen ZhengDepartment of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Xijing Hospital · CNAir Force Medical University · CNLonggang Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo evaluate the predictive value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) quantitative parameters in treatment response to concurrent chemoradiotherapy (CCRT) for locally advanced cervical squamous cell carcinoma (LACSC). METHODS AND MATERIALS: LACSC patients underwent CCRT had DCE-MRI before (e0) and after 3 days of treatment (e3). Extended Tofts Linear model with a user arterial input function was adopted to generate quantitative measurements. Endothelial transfer constant (K

resultsK

conclusionsQuantitative parameters at e0 and e3 from DCE-MRI could be used as potential indicators for predicting treatment response of LACSC.

Indexed as

cervical cancerconcurrent chemoradiotherapydynamic contrast-enhanced magnetic resonance imagingTofts DCE-MRI modeltreatment response

Identifiers

PMID33194734
PMCPMC7658627
OpenAlexW3096650538

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.