Evidence map›Paper›PMID 31019776›Full record

ArticleJournal of thoracic disease2019

Trends in lung cancer screening in the United States, 2016-2017.

Ikenna C Okereke, Shawn Nishi, Jie Zhou, James S Goodwin

Registry-linked trialAbstract read
In one paragraph

Article in Journal of thoracic disease, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05824273 (Leveraging Social Media to Increase Lung Cancer Screening Awareness, Knowledge and Uptake in High-Risk Populations), which is not on this map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing 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.

NCT05824273 nacompletednot on this mapstarted 2023, after this paper: background citation

Leveraging Social Media to Increase Lung Cancer Screening Awareness, Knowledge and Uptake in High-Risk Populations

TypeinterventionalSponsorHackensack Meridian HealthRan2023 to 2024Enrolled512ConditionsLung CancerArmsLungTalk, Non-tailored intervention - Standard of practice
3 · Its place in the literature

Who cites it

49 citing papers in PubMed.

  1. Article
  2. Exploring Clinical Pathways to a Metastatic Lung Cancer Diagnosis: A Latent Class Analysis Using North Carolina Multipayer Claims Data.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Using Telehealth to Increase Lung Cancer Screening Referrals for At-Risk Veterans in Rural Communities.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2024
    Article
  12. Advanced Bronchoscopic Diagnostic Techniques in Lung Cancer.Tuberculosis and respiratory diseases · 2024
    Article
  13. Outcomes in Incidentally Versus Screening Detected Stage I Lung Cancer Surgery Patients.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2024
    Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Training and Dissemination of Lung Cancer Education Curriculum Among Community Health Advisors in the Deep South: a Program Evaluation.Journal of cancer education : the official journal of the American Association for Cancer Education · 2023
    Article
  20. 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.

Ikenna C OkerekeDivision of Cardiothoracic Surgery, University of Texas Medical Branch, Galveston, TX, USA.
Shawn NishiDivision of Pulmonary, Critical Care and Sleep Medicine, University of Texas Medical Branch, Galveston, TX, USA.
Jie ZhouSealy Center on Aging, University of Texas Medical Branch, Galveston, TX, USA.
James S GoodwinDepartment of Internal Medicine, University of Texas Medical Branch, Galveston, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung cancer is the most common cancer killer annually, yet the overall rate of eligible patients who undergo screening with low-dose computed tomography (LDCT) is low. Our goal was to determine factors which were associated with the probability of obtaining lung cancer screening.

methodsThe Clinformatics Data Mart (CDM) database, a national commercial health insurance database with over 18,000,000 enrollees, was queried to determine the rate of LDCT screening and factors which influenced receiving LDCT screening. All enrollees between the ages of 55 and 77 from 2016 to 2017 were included. Demographics, history of tobacco exposure and state smoking statistics were recorded.

resultsAll 8,350,197 enrollees aged 55-77 were included in the study. Among enrollees, the rate of screening increased throughout 2016 and early 2017 and then appeared to stabilize. In the second half of 2017 the LDCT rate was approximately 6 per 1,000 enrollees per year, and was increasing at a slope of 0.1 additional LDCT per 1,000 enrollees per year. There was marked geographic variation, with 5-fold differences in LDCT rates between different regions. There was no correlation between smoking rate and LDCT rate at the state level (r=0.02; P=0.87). Enrollees aged 65-69 were most likely to be screened (OR =1.53; 1.45-1.61) compared to enrollees aged 55-59.

conclusionsThe rate of LDCT screening is increasing very slowly with time, and most eligible patients are not screened. Further studies are needed to determine the reasons for low screening rates, and the marked geographic variation.

Indexed as

Early detection of cancerlung neoplasmstobacco smoking

Identifiers

PMID31019776
PMCPMC6462682

What OpenQuestion holds

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Registered trials

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.