Evidence map›Paper›PMID 35510544›Full record

ArticleNursing research

A Multilevel Approach to Investigate Relationships Between Healthcare Resources and Lung Cancer.

Darryl Somayaji, Young S Seo, Gregory E Wilding, Ekaterina Noyes

Abstract read
In one paragraph

Article in Nursing research. 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.

  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.

Funding

University of Buffalo Clinical and Translational Science Institute - Supplement SchulyerUL1TR001412 · NCATS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI MURPHY, TIMOTHY F · 2015 to 2024
$33.8M
Institutional Career DevelopmentKL2TR001413 · NCATS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI DUBOCOVICH, MARGARITA L · 2015 to 2024
$4.2M
NCATS NIH HHS KL2 TR001413NCATS NIH HHS UL1 TR001412
6 · The paper itself

Abstract

backgroundScreening for lung cancer is an evidence-based but underutilized measure to reduce the burden of lung cancer mortality. Lack of adequate data on geographic availability of lung cancer screening inhibits the ability of healthcare providers to help patients with decision-making and impedes equity-focused implementation of screening-supportive services.

objectivesThis analysis used data from the 2012-2016 Surveillance, Epidemiology, and End Results (SEER) Program, the Behavioral Risk Factor Surveillance System, and the county health ranking to examine (a) which cancer resources and county-level factors are associated with late-stage lung cancer at diagnosis and (b) associations between county rurality and lung cancer incidence/mortality rates.

methodsUsing the New York state SEER data, we identified 68,990 lung cancer patients aged 20-112 years; 48.3% had late-stage lung cancers, and the average lung cancer incidence and mortality rates were 70.7 and 46.2 per 100,000, respectively. There were 144 American College of Radiology-designated lung cancer screening centers and 376 Federally Qualified Health Centers identified in New York state. County rurality was associated with a higher proportion of late-stage lung cancers and higher lung cancer mortality rates. DISCUSSION: Visual geomapping showed the scarcity of rural counties' healthcare resources. County rurality is a significant factor in differences in lung cancer screening resources and patient outcomes. Use of publicly available data with geospatial methods provides ways to identify areas for improvement, populations at risk, and additional infrastructure needs.

Indexed as

Lung NeoplasmsDelivery of Health CareEarly Detection of CancerHumansIncidenceRural Population

Identifiers

PMID35510544
PMCPMC9420764

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.