Evidence map›Paper›PMID 39594683›Full record

ArticleCancers2024

Changes in Staging and Management of Non-Small Cell Lung Cancer (NSCLC) Patients Following the Implementation of Low-Dose Chest Computed Tomography (LDCT) Screening at Kaohsiung Medical University Hospital.

Chin-Ling Chen, Jui-Sheng Hsu, Yi-Wen Shen, Chih-Hsiang Hsu, Shih-Yu Kao, Wei-An Lai, Cheng-Hao Chuang, Yu-Wei Liu, Jui-Ying Lee, Shah-Hwa Chou and 3 more

Abstract read
In one paragraph

Article in Cancers, 2024. 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
–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

11 citing papers in PubMed.

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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

13 authors.

Chin-Ling ChenCancer Center, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.
Jui-Sheng HsuDepartment of Radiology, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.
Yi-Wen ShenCancer Center, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.ORCID 0009-0005-8656-0395
Chih-Hsiang HsuCancer Center, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.
Shih-Yu KaoCancer Center, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.ORCID 0009-0008-7618-2206
Wei-An LaiDepartment of Pathology, Kaohsiung Kaohsiung Medical University, Kaohsiung 80708, Taiwan.
Cheng-Hao ChuangDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.ORCID 0000-0003-4239-4012
Yu-Wei LiuDivision of Thoracic Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.ORCID 0000-0001-9908-2322
Jui-Ying LeeDivision of Thoracic Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.
Shah-Hwa ChouDivision of Thoracic Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.
Jen-Yu HungDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.
Inn-Wen ChongDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.ORCID 0000-0001-8328-8684
Chih-Jen YangDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.ORCID 0000-0002-3576-7936

Funding

National Science and Technology Council NSTC 113-2314-B-037 -104 -MY3
6 · The paper itself

Abstract

backgroundLow-dose computed tomography (LDCT) has been widely adopted for lung cancer screening due to its proven ability to reduce lung cancer mortality, especially among high-risk populations.

methodsThis retrospective study aims to evaluate the impact of LDCT screening on non-small cell lung cancer (NSCLC) staging at Kaohsiung Medical University Hospital (KMUH) from 2011 to 2020, following the introduction of LDCT in 2013. The study examines the correlation between LDCT screening volume and changes in the distribution of NSCLC stages, particularly early-stage (stages 0 and I) and late-stage (stage IV) diagnoses. Additionally, it explores the differences in histopathological subtypes, focusing on adenocarcinoma and squamous cell carcinoma, and assesses the impact of early detection on five-year survival rates.

resultsThe results show a significant increase in early-stage NSCLC diagnoses, particularly in adenocarcinoma cases, where early-stage diagnoses rose from 10.4% in 2010 to 38.7% in 2019. However, the number of stage IV cases remained stable, indicating that LDCT may not substantially reduce late-stage diagnoses. Pearson's correlation analysis demonstrated a strong positive correlation between LDCT screening and early-stage NSCLC detection, particularly for adenocarcinoma (

conclusionsThe study concludes that LDCT screening plays a crucial role in improving early NSCLC detection and five-year survival rates. Future research should focus on optimizing screening strategies to capture more at-risk populations and enhance the detection of harder-to-diagnose subtypes like squamous cell carcinoma.

Indexed as

adenocarcinomaearly detectionfive-year survivalLDCTlow-dose computed tomographylung cancer stagingnon-small cell lung cancersquamous cell carcinoma

Identifiers

PMID39594683
PMCPMC11592150

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.