Evidence map›Paper›PMID 39430340›Full record

ArticleTranslational lung cancer research2024

Qiwei Yang, Ziyi Wang, Qiang Fu, Xiaohai Hu, Liang Chen, Weiyang Chen, Ling Lv, Zhenghua Liu, Wanfu Men, Danni Li and 1 more

Abstract read
In one paragraph

Article in Translational lung cancer research, 2024. 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
–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

4 citing papers in PubMed.

  1. OsimertinibTranslational lung cancer research · 2026
    Article
  2. Article
  3. Article
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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.

Qiwei YangDepartment of Thorax, The First Hospital of China Medical University, Shenyang, China.
Ziyi WangDepartment of Thorax, The First Hospital of China Medical University, Shenyang, China.
Qiang FuDepartment of Thorax, The First Hospital of China Medical University, Shenyang, China.
Xiaohai HuDepartment of Thorax, The First Hospital of China Medical University, Shenyang, China.
Liang ChenDepartment of Thorax, The First Hospital of China Medical University, Shenyang, China.
Weiyang ChenDepartment of Thorax, The First Hospital of China Medical University, Shenyang, China.
Ling LvDepartment of Thorax, The First Hospital of China Medical University, Shenyang, China.
Zhenghua LiuDepartment of Thorax, The First Hospital of China Medical University, Shenyang, China.
Wanfu MenDepartment of Thorax, The First Hospital of China Medical University, Shenyang, China.
Danni LiDepartment of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
Wenya LiDepartment of Thorax, The First Hospital of China Medical University, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Malignant pleural effusion (MPE) is associated with poor prognosis in patients with advanced lung adenocarcinoma (LUAD), and abnormal activation of epidermal growth factor receptor (EGFR) plays a crucial role in the development of LUAD. This study aimed to investigate the correlation between Methods: A case-control study design was adopted that included patients pathologically diagnosed with LUAD. Clinical data were collected, and patients were divided into the MPE group and the non-MPE (N-MPE) group based on the presence of MPE. Propensity score matching (PSM) was used to control for confounding factors. The correlation between Results: A total of 849 patients were included in the study. After 1:2 PSM, there were 180 patients in the MPE group and 360 in the N-MPE group. The Conclusions: This study found there to be a positive correlation between

Indexed as

EGFR mutationLung adenocarcinoma (LUAD)malignant pleural effusion (MPE)T790M mutation

Identifiers

PMID39430340
PMCPMC11484724

What OpenQuestion holds

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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.