Evidence map›Paper›PMID 37989340›Full record

ArticleZhongguo fei ai za zhi = Chinese journal of lung cancer2023

[Progress in Diagnosis and Treatment of Lung Cancer Associated with Cystic Airspaces].

Jinxu Yang, Ying Chen, Yujie Lei, Yunchao Huang

Open access · greenAbstract readEnglish Abstract
In one paragraph

Article in Zhongguo fei ai za zhi = Chinese journal of lung cancer, 2023. 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, 2 citations in OpenAlex.

  1. Article
  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

4 authors at 1 institution in 1 country.

Jinxu YangDepartment of Thoracic Surgery I, The Third Affiliated Hospital of Kunming Medical University, Kunming 650118, China.
Ying ChenDepartment of Thoracic Surgery I, The Third Affiliated Hospital of Kunming Medical University, Kunming 650118, China.
Yujie LeiDepartment of Thoracic Surgery I, The Third Affiliated Hospital of Kunming Medical University, Kunming 650118, China.
Yunchao HuangDepartment of Thoracic Surgery I, The Third Affiliated Hospital of Kunming Medical University, Kunming 650118, China.
Kunming Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer associated with cystic airspaces (LCCA) is a type of lung cancer characterized by the presence of cystic cavities in or around the tumor on imaging. Due to its high potential for misdiagnosis or underdiagnosis, the prognosis of LCCA patients is poor, necessitating further large-scale clinical studies to elucidate its characteristics. Currently, four imaging classification systems exist, and there has been a progressive increase in attention towards LCCA, particularly with regard to the study of its imaging features. The results indicate a correlation between the pathological features and imaging findings of LCCA; however, research on driver gene mutations and molecular subtyping associated with lung cancer remains insufficient. Due to the challenges associated with early diagnosis and the poorer prognosis compared to general types of lung cancer, this paper comprehensively reviews the research progress on LCCA, including its definition, etiology, pathogenesis, imaging features, histological and pathological features, treatment, and prognosis, aiming to serve as a valuable resource for clinical decision-making.
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Indexed as

Lung NeoplasmsHumansPrognosisTomography, X-Ray ComputedClinicopathological featuresEarly diagnosisImage characteristicsLung cancer associated with cystic airspacesLung neoplasmsPathogenesisPrognosis

Identifiers

PMID37989340
PMCPMC10663780
OpenAlexW4388921824

What OpenQuestion holds

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LicenceCC BY
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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.