ReviewCureus2026
Lung Cancer Screening in California and Los Angeles County: A Landscape Analysis.
Review in Cureus, 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung cancer screening with low-dose computed tomography (LDCT) reduces mortality, yet California has among the nation's lowest screening rates with substantial disparities by race, ethnicity, and socioeconomic status. This landscape analysis characterizes the current lung cancer screening implementation ecosystem in California and Los Angeles (LA) County to inform stakeholders seeking to improve screening equity. We conducted a structured review of peer-reviewed literature and grey literature following methods adapted from Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines, synthesizing information on cancer screening policy frameworks, healthcare system structure, delivery infrastructure, risk factor distribution, and screening outcomes. The analysis examines lung cancer screening in the context of established screening programs (breast, colorectal, cervical cancer) and describes California's complex healthcare landscape with emphasis on safety-net systems serving the highest-risk populations. Lung cancer screening currently lacks infrastructure elements present in established programs, including comprehensive federal legislative frameworks, quality regulation comparable to the Mammography Quality Standards Act (MQSA), and fully developed performance measures. California's healthcare system presents specific implementation challenges: MediCal reimbursement ranks 40th nationally with declining provider participation; multi-layered contractual arrangements create care coordination complexity; and federally qualified health centers face margin pressures while providing nearly half of MediCal primary care. LA County demonstrates profound geographic maldistribution-LDCT facilities cluster in low-risk areas while communities with the highest tobacco exposure and poorest air quality have the least access to screening resources. Tobacco retailers are concentrated in low-income areas, and three-quarters of those at-risk from poor air quality are people of color. Current performance reflects these barriers: California's screening rates rank among the nation's worst, 68% of LA diagnoses are late-stage, and substantial racial disparities exist. This landscape analysis provides stakeholders with comprehensive documentation of the policy frameworks, system structures, risk distributions, and implementation barriers that define the lung cancer screening ecosystem in the United States' most populous county, serving as a foundation for evidence-informed efforts to improve screening equity.
Indexed as
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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.