Evidence map›Paper›PMID 39128912›Full record

ArticleScientific reports2024

A novel predictor for dosimetry data of lung and the radiation pneumonitis incidence prior to SBRT in lung cancer patients.

Xiong Yang, Zeyi Dai, Hongbing Song, Hongyun Gong, Xiangpan Li

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Trial
  2. 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

5 authors.

Xiong Yang *Department of Radiation Oncology, Renmin Hospital of Wuhan University, No. 238 Jiefang Road, Wuchang District, Wuhan, 430060, Hubei, China.
Zeyi Dai *The Institute for Advanced Studies, Wuhan University, Wuhan, 430072, Hubei, China.
Hongbing SongDepartment of Radiation Oncology, Renmin Hospital of Wuhan University, No. 238 Jiefang Road, Wuchang District, Wuhan, 430060, Hubei, China.
Hongyun GongDepartment of Radiation Oncology, Renmin Hospital of Wuhan University, No. 238 Jiefang Road, Wuchang District, Wuhan, 430060, Hubei, China. dr_gonghongyun@163.com.
Xiangpan LiDepartment of Radiation Oncology, Renmin Hospital of Wuhan University, No. 238 Jiefang Road, Wuchang District, Wuhan, 430060, Hubei, China. rm001227@whu.edu.cn.

Funding

The Research Foundation on Cutting-edge Cancer Supportive Care cphcf-2022-146
6 · The paper itself

Abstract

Normal tissue complication probability (NTCP) models for radiation pneumonitis (RP) in lung cancer patients with stereotactic body radiation therapy (SBRT), which based on dosimetric data from treatment planning, are limited to patients who have already received radiation therapy (RT). This study aims to identify a novel predictive factor for lung dose distribution and RP probability before devising actionable SBRT plans for lung cancer patients. A comprehensive correlation analysis was performed on the clinical and dose parameters of lung cancer patients who underwent SBRT. Linear regression models were utilized to analyze the dosimetric data of lungs. The performance of the regression models was evaluated using mean squared error (MSE) and the coefficient of determination (R

Indexed as

Lung NeoplasmsRadiation PneumonitisRadiometryRadiosurgeryAgedAged, 80 and overFemaleHumansIncidenceLungMaleMiddle AgedRadiotherapy DosageRadiotherapy Planning, Computer-AssistedLung cancerLung tumor ratioMachine learning modelsRadiation pneumonitisStereotactic body radiation therapy

Identifiers

PMID39128912
PMCPMC11317486

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Registered trials

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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.