Evidence map›Paper›PMID 35087743›Full record

ArticleFrontiers in oncology2021

Potential Defects and Improvements of Equivalent Uniform Dose Prediction Model Based on the Analysis of Radiation-Induced Brain Injury.

Qing-Hua Du, Jian Li, Yi-Xiu Gan, Hui-Jun Zhu, Hai-Ying Yue, Xiang-De Li, Xue Ou, Qiu-Lu Zhong, Dan-Jing Luo, Yi-Ting Xie and 3 more

Abstract 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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

13 authors.

Qing-Hua DuDepartment of Radiation Oncology, Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Jian LiDepartment of Radiation Oncology, Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Yi-Xiu GanDepartment of Radiation Oncology, Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Hui-Jun ZhuDepartment of Radiation Oncology, Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Hai-Ying YueDepartment of Radiation Oncology, Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Xiang-De LiDepartment of Radiation Oncology, Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Xue OuDepartment of Radiation Oncology, Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Qiu-Lu ZhongDepartment of Radiation Oncology, Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Dan-Jing LuoDepartment of Radiation Oncology, Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Yi-Ting XieDepartment of Radiation Oncology, Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Qian-Fu LiangDepartment of Radiation Oncology, Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Ren-Sheng WangDepartment of Radiation Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Wen-Qi LiuDepartment of Radiation Oncology, Second Affiliated Hospital of Guangxi Medical University, Nanning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo study the impact of dose distribution on volume-effect parameter and predictive ability of equivalent uniform dose (EUD) model, and to explore the improvements. METHODS AND MATERIALS: The brains of 103 nasopharyngeal carcinoma patients treated with IMRT were segmented according to dose distribution (brain and left/right half-brain for similar distributions but different sizes; V

resultsThe mAUC of brain/half-brain EUD was 0.819/0.821 and the optimal

conclusionVolume-effect parameter of EUD is variable and related to dose distribution. EUD with large low-dose volume may not be better than simple dose/volume points. Critical-dose-volume EUD could improve the predictive ability and has an invariant volume-effect parameter. Mean dose may be the case in which critical-dose-volume EUD has the best predictive ability.

Indexed as

brain injuryequivalent uniform dosenasopharyngeal carcinomapredictive abilityvolume-effect parameter

Identifiers

PMID35087743
PMCPMC8786722

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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.