ArticleJournal of thoracic disease2026
Demographic shifts in referral to and completion of lung cancer screening after the 2021 United States Preventive Services Task Force update.
Article in Journal of thoracic disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The United States Preventive Services Task Force (USPSTF) expanded the age and pack-year criteria for lung cancer screening (LCS) in 2021 in part to improve equity in eligibility for women and racial minority groups. Prior research has examined characteristics of patients who participated in LCS (screened) based on completed low-dose computed tomography (LDCT) pre- and post-USPSTF update in majority White patient populations, but has not done so in more diverse settings. No prior studies have assessed changes in referral patterns related to the update. We therefore examined both screening and referral patterns pre- Methods: We analyzed LCSP registry data from 2014 to 2023 in a large, urban outpatient health system in Washington, DC, USA with a majority Black population. We performed a pre-/post-update comparison of sex and race among screened patients, defined as those who completed LDCT. We additionally compared pre-/post-update sex and race among referred patients, regardless of whether they completed LDCT. We modeled the odds of LDCT completion after referral with logistic regression, stratified by pre-/post- group. Results: The proportion of female patients referred significantly increased from 43% pre-update to 53% post-update, and in Black patients from 67% to 74%. Increases in referrals directly translated to significant increases in screening, where the proportion of female patients screened also rose from 40% pre-update to 53% post-update, and in Black patients from 65% to 74%. Screening rates (percent screened among referred) in female patients rose from 66% pre-update to 90% post-update, and in Black patients from 69% to 90%. In multivariable analysis among referred patients, the odds of LDCT completion were not independently associated with sex or race either pre- or post-update after adjusting for other demographic factors and smoking history [female ( Conclusions: We found that following the 2021 USPSTF update to LCS eligibility criteria, the proportion of Black and female individuals increased among both screened and referred patients in an urban, majority Black setting. Observed increases were even greater than that reported in prior literature from majority White populations. Our findings add evidence that changes in guidelines can translate to real-world improvement in equitable access to early detection of lung cancer.
Indexed as
Identifiers
What OpenQuestion holds
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.