Evidence map›Paper›PMID 40083500›Full record

ArticleJournal of thoracic disease2025

Identifying lung cancer in Emergency Department patients outside national lung cancer screening guidelines.

Hao Wang, Radhika Cheeti, Miles Murray, Timothy A Muirheid, Jasmine McDowell, Usha Sambamoorthi

Abstract read
In one paragraph

Article in Journal of thoracic disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Hao WangDepartment of Emergency Medicine, John Peter Smith Health Network, Fort Worth, TX, USA.ORCID https://orcid.org/0000-0002-5105-0951
Radhika CheetiDepartment of Information Technology, John Peter Smith Health Network, Fort Worth, TX, USA.
Miles MurrayDepartment of Emergency Medicine, John Peter Smith Health Network, Fort Worth, TX, USA.
Timothy A MuirheidDepartment of Information Technology, John Peter Smith Health Network, Fort Worth, TX, USA.
Jasmine McDowellDepartment of Emergency Medicine, John Peter Smith Health Network, Fort Worth, TX, USA.
Usha SambamoorthiCollege of Pharmacy, University of North Texas Health Science Center, Fort Worth, TX, USA.

Funding

AIM-AHEAD Coordinating Center - All Four CoresOT2OD032581 · OD · UNIVERSITY OF NORTH TEXAS HLTH SCI CTR · PI Paul Avillach, Bettina M. Beech · 2021 to 2026
$168.7M
Texas Minority Health, Research and Outreach (MiHERO)S21MD012472 · NIMHD · UNIVERSITY OF NORTH TEXAS HLTH SCI CTR · PI JAMBOOR K. VISHWANATHA · 2017 to 2026
$18.0M
NIH HHS OT2 OD032581NIMHD NIH HHS S21 MD012472
6 · The paper itself

Abstract

Background: Lung cancer has become the second most common cancer and the leading cause of cancer death in the United States. We aim to determine factors associated with newly diagnosed lung cancer at the Emergency Department (ED) and identify specific patient populations eligible for lung cancer diagnostic screening. Methods: This is a single-center retrospective observational study. We included all patients aged between 50 and 80 years old, who presented to the ED seeking healthcare between January 1, 2019, and December 31, 2023. Patients' socio-demographics, clinical information, and whether they were eligible for lung cancer screening determined by the United States Preventive Services Task Force (USPSTF) guideline were analyzed and compared between patients who had newly diagnosed lung cancer at ED and those without. Factors associated with newly diagnosed lung cancer patients were determined by multivariable logistic regressions with inverse probability weighting (IPW) to account for observed selection bias of lung cancer screening eligibility. Results: Out of 75,516 patients in this study, 18,641 (25%) patients had documented smoking histories. Among these, only 8,051 (10.66%) were eligible for lung cancer screening, while 18,348 patients received lung computer tomography (CT). Among all patients whose CTs were performed, 123 individuals were identified as having been newly diagnosed with lung cancer. Multivariable logistic regressions showed that the adjusted odds ratio (AOR) for eligible lung cancer diagnostic screening was 3.07 [95% confidence interval (CI): 2.08-4.53, P<0.001] without IPW and 3.49 (95% CI: 2.24-5.42, P<0.001) with IPW. Other factors associated with newly diagnosed lung cancer in ED were older age, female, and patients who spoke neither English nor Spanish. Conclusions: To optimize the identification of suitable patients for lung cancer diagnostic screening in the ED, it may be beneficial to modify the eligibility criteria beyond those currently outlined by the USPSTF guidelines. Integrating additional factors such as advanced age, female sex, and a preference for non-English languages could improve the screening's effectiveness by capturing at-risk populations that might otherwise be overlooked.

Indexed as

Emergency Department (ED)Lung cancerscreening eligibility

Identifiers

PMID40083500
PMCPMC11898393

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.