Evidence map›Paper›PMID 40146107›Full record

ArticleJAMA network open2025

Individual- and Group-Level Disparities Between Racial and Ethnic Groups in Lung Cancer Screening Eligibility Criteria.

Corey D Young, Hormuzd A Katki, Li C Cheung, M Patricia Rivera, Hilary A Robbins, Melinda C Aldrich, Jeffrey D Blume, Anil K Chaturvedi, Rebecca Landy

Abstract read
In one paragraph

Article in JAMA network open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Addressing algorithmic bias in lung cancer screening eligibility.Journal of the National Cancer Institute · 2026
    Article
  6. 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

9 authors.

Corey D YoungDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland.
Hormuzd A KatkiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland.
Li C CheungDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland.
M Patricia RiveraDivision of Pulmonary and Critical Care Medicine, University of Rochester Medical Center, Rochester, New York.
Hilary A RobbinsGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.
Melinda C AldrichDepartment of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Tennessee.
Jeffrey D BlumeSchool of Data Science, University of Virginia, Charlottesville.
Anil K ChaturvediDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland.
Rebecca LandyDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland.

Funding

Addressing racial disparities in lung cancer screeningR01CA251758 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ALDRICH, MELINDA, BLUME, JEFFREY D. · 2021 to 2025
$2.4M
Understanding determinants of racial disparities in lung cancer incidenceU01CA253560 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ALDRICH, MELINDA · 2020 to 2023
$2.3M
Comorbidity and Functional Status in a Population Undergoing Lung Cancer ScreeningR01CA251686 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HENDERSON, LOUISE, RIVERA, MARIA PATRICIA · 2020 to 2023
$1.5M
Evaluating risk prediction models for use in lung cancer screening in diverse populations around the worldR03CA245979 · NCI · INTERNATIONAL AGENCY FOR RES ON CANCER · PI ROBBINS, HILARY A. · 2020 to 2020
$112k
NCI NIH HHS R01 CA251686NCI NIH HHS R01 CA251758NCI NIH HHS R03 CA245979NCI NIH HHS U01 CA253560World Health Organization 001
6 · The paper itself

Abstract

Importance: Lung cancer screening guidelines result in differential screening eligibility among individuals who might benefit equally from screening and in population-level differences in screening eligibility and benefit across races and ethnicities. Objective: To inform lung cancer screening policy development by evaluating how enforcing (1) equal lung cancer screening eligibility for all individuals with equal benefit and (2) equal program sensitivity across racial and ethnic subgroups are associated with screening eligibility and benefit. Design, Setting, and Participants: This cross-sectional comparative effectiveness study included 6915 members of the US noninstitutionalized population aged 50 to 80 years who ever smoked and who participated in the 2015 National Health Interview Survey. Statistical analysis was performed from May 2022 to April 2024. Exposure: Lung cancer screening eligibility is based on the LYFS-CT (life-years gained from screening-computed tomography) prediction model, which predicts gain in life expectancy from screening, where individuals are eligible if their predicted benefit exceeds a threshold across all possible thresholds. Main Outcomes and Measures: The proportion of individuals aged 50 to 80 years who ever smoked who are eligible for screening, the percentage of predicted gainable life gained from screening (program sensitivity), and the number needed to screen to gain 10 years of life (screening efficiency), by race and ethnicity. Results: The 6915 participants aged 50 to 80 years who ever smoked represented 44 million individuals (mean age, 63 years [IQR, 56-69 years]; 53% male; 68% formerly smoked; 10% African American individuals, 3% Asian American individuals, 8% Hispanic American individuals, and 79% non-Hispanic White individuals). To ensure equal screening eligibility for each race and ethnicity required race- and ethnicity-specific eligibility thresholds. To achieve 36% eligibility for each race and ethnicity, the required days of life gained (under the LYFS-CT model) screening eligibility thresholds would be 5.2 for Hispanic American individuals, 5.6 for Asian American individuals, 9.5 for non-Hispanic White indivduals, and 12.4 for African American individuals, so individuals of different races and ethnicities with the same benefit would have different eligibility. With a fixed eligibility threshold of 16.2 days, screening eligibility would differ across races and ethnicities; 7% of Hispanic American individuals, 9% of Asian American individuals, 20% of non-Hispanic White individuals, and 27% of African American individuals aged 50 to 80 years who ever smoked would be eligible for screening. Similar differences existed for the program sensitivity of screening benefit. African American individuals consistently maintained the most efficient number needed to screen across all thresholds; Hispanic American individuals had the least efficient number needed to screen and thus may experience the worst benefit-harm balance when equalizing program sensitivity between races and ethnicities. Conclusions and Relevance: This comparative effectiveness study of lung cancer screening eligibility suggests that screening eligibility criteria cannot result in both equal eligibility for all individuals with the same benefit and equal program sensitivity for each race and ethnicity. In general, race- and ethnicity-specific thresholds that result in equal group-level sensitivity on 1 metric cannot result in equal sensitivities on other metrics. Thus, only 1 metric can be equalized, requiring a value judgment on which to prioritize.

Indexed as

Early Detection of CancerEligibility DeterminationEthnicityHealthcare DisparitiesLung NeoplasmsMass ScreeningRacial GroupsAgedAged, 80 and overCross-Sectional StudiesFemaleHumansMaleMiddle AgedUnited States

Identifiers

PMID40146107
PMCPMC11950895

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.