Evidence map›Paper›PMID 33342671›Full record

ArticleAmerican journal of preventive medicine2021

Variation in Eligible Patients' Agreeing to and Receiving Lung Cancer Screening: A Cohort Study.

N Joseph Leishman, Renda S Wiener, Angela Fagerlin, Rodney A Hayward, Julie Lowery, Tanner J Caverly

Open access · greenAbstract read
In one paragraph

Article in American journal of preventive medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.3field-weighted citation impact, top 16% of its field
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

13 citing papers in PubMed, 14 citations in OpenAlex.

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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

6 authors at 4 institutions in 1 country.

N Joseph LeishmanCenter for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan; University of Michigan School of Public Health, Ann Arbor, Michigan.
Renda S WienerThe Pulmonary Center, Boston University School of Medicine, Boston, Massachusetts; Center for Healthcare Organization and Implementation Research, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, Massachusetts.
Angela FagerlinDepartment of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, Utah; Informatics Decision-Enhancement and Analytic Sciences (IDEAS) Center for Innovation, VA Salt Lake City Healthcare System, Salt Lake City, Utah.
Rodney A HaywardCenter for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan; Departments of Learning Health Sciences and Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan.
Julie LoweryCenter for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan.
Tanner J CaverlyCenter for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan; Departments of Learning Health Sciences and Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan. Electronic address: tcaverly@med.umich.edu.
University of Michigan–Ann Arbor · USVA Ann Arbor Healthcare System · USBoston University · USCenter for Innovation · US

Funding

Implementing Shared Decision-Making for Cancer Screening in Primary CareIK2HX002246 · VA · VETERANS HEALTH ADMINISTRATION · PI CAVERLY, TANNER J · 2018 to 2022
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HSRD VA IK2 HX002246
6 · The paper itself

Abstract

introductionLittle is known about how clinicians make low-dose computed tomography lung cancer screening decisions in practice. Investigators assessed the factors associated with real-world decision making, hypothesizing that lung cancer risk and comorbidity would not be associated with agreeing to or receiving screening. Though these factors are key determinants of the benefit of lung cancer screening, they are often difficult to incorporate into decisions without the aid of decision tools.

methodsThis was a retrospective cohort study of patients meeting current national eligibility criteria and deemed appropriate candidates for lung cancer screening on the basis of clinical reminders completed over a 2-year period (2013-2015) at 8 Department of Veterans Affairs medical facilities. Multilevel mixed-effects logistic regression models (conducted in 2019-2020) assessed predictors (age, sex, lung cancer risk, Charlson Comorbidity Index, travel distance to facility, and central versus outlying decision-making location) of primary outcomes of agreeing to and receiving lung cancer screening.

resultsOf 5,551 patients (mean age=67 years, 97% male, mean lung cancer risk=0.7%, mean Charlson Comorbidity Index=1.14, median travel distance=24.2 miles), 3,720 (67%) agreed to lung cancer screening and 2,398 (43%) received screening. Lung cancer risk and comorbidity score were not strong predictors of agreeing to or receiving screening. Empirical Bayes adjusted rates of agreeing to and receiving screening ranged from 22% to 84% across facilities and from 19% to 85% across clinicians. A total of 33.7% of the variance in agreeing to and 34.2% of the variance in receiving screening was associated with the facility or the clinician offering screening.

conclusionsSubstantial variation was found in Veterans agreeing to and receiving lung cancer screening during the Veterans Affairs Lung Cancer Screening Demonstration Project. This variation was not explained by differences in key determinants of patient benefit, whereas the facility and clinician advising the patient had a large impact on lung cancer screening decisions.

Indexed as

Early Detection of CancerLung NeoplasmsAgedBayes TheoremCohort StudiesFemaleHumansMaleMass ScreeningRetrospective Studies

Identifiers

PMID33342671
PMCPMC10440012
OpenAlexW3112532674

What OpenQuestion holds

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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.