Trial reportBMC cancer2022
Racial difference in BMI and lung cancer diagnosis: analysis of the National Lung Screening Trial.
Trial report in BMC cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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
9 citing papers in PubMed, 9 citations in OpenAlex.
- Obesity Promotes Lung Carcinogenesis Through Airway Immune Dysfunction.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2026Article
- Female-specific risk factors for lung cancer: insights from the All of Us Research Program.BMC public health · 2026Article
- Metabolome-Wide Mendelian Randomization Identifies Maleate as a Mediator of the Effect of Obesity on the Risk of Small Cell Lung Cancer.Food science & nutrition · 2025Article
- Glucagon-like peptide-1 receptor agonism improves lung cancer outcomes and tumor growth control.JCI insight · 2025Article
- Characteristics associated with early vs. late adoption of lung cancer screening.Preventive medicine reports · 2024Article
- A Retrospective Analysis: Investigating Factors Linked to High Lung-RADS Scores in a Nonsmoking, Non-Family History Population.Diagnostics (Basel, Switzerland) · 2024Article
- Prospective evaluation of deep learning image reconstruction for Lung-RADS and automatic nodule volumetry on ultralow-dose chest CT.PloS one · 2024Article
- Obesity and lung cancer-a narrative review.Journal of thoracic disease · 2023Review
- Mendelian randomization to explore the direct or mediating associations between socioeconomic status and lung cancer.Frontiers in oncology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThe inverse relationship between BMI and lung cancer diagnosis is well defined. However, few studies have examined the racial differences in these relationships. The purpose of this paper is to explore the relationships amongst race, BMI, and lung cancer diagnosis using the National Lung Screening Trial (NLST) data.
methodsMultivariate regression analysis was used to analyze the BMI, race, and lung cancer diagnosis relationships.
resultsAmong 53,452 participants in the NLST cohort, 3.9% were diagnosed with lung cancer, 43% were overweight, and 28% were obese. BMI was inversely related to lung cancer diagnosis among Whites: those overweight (aOR = .83, 95%CI = .75-.93), obese (aOR = .64, 95%CI = .56-.73) were less likely to develop lung cancer, compared to those with normal weight. These relationships were not found among African-Americans.
conclusionOur findings indicate that the inverse relationship of BMI and lung cancer risk among Whites is consistent, whereas this relationship is not significant for African-Americans. In consideration of higher lung cancer incidence among African Americans, we need to explore other unknown mechanisms explaining this racial difference.
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.