ArticleAnnals of internal medicine2018
Identifying Patients for Whom Lung Cancer Screening Is Preference-Sensitive: A Microsimulation Study.
Article in Annals of internal medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07073898 (Population Health Management Approaches to Increase Lung Cancer Screening in Community Health Centers - UG3 Pilot Clinical Trial), which is not on this map. Cited by 69 papers, 3 of them syntheses that pooled it.
What it found
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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.
Population Health Management Approaches to Increase Lung Cancer Screening in Community Health Centers - UG3 Pilot Clinical Trial
Who cites it
69 citing papers in PubMed, 3 syntheses or guidelines pooled it, 92 citations in OpenAlex.
- The influence of postscreening follow-up time and participant characteristics on estimates of overdiagnosis from lung cancer screening trials.International journal of cancer · 2022Pooled it
- Guideline
- Guideline
- Why Women Appear to Have Better Outcomes When Undergoing Screening for Lung Cancer.Annals of the American Thoracic Society · 2025Trial
- Trial
- Cost-Effectiveness of a Telephone-Based Smoking Cessation Randomized Trial in the Lung Cancer Screening Setting.JNCI cancer spectrum · 2022Trial
- Feasibility and acceptability of an everyday patient-centered discussion model for primary care: An exploratory, single-center study in the VA primary care setting.PEC innovation · 2026Article
- Bias in Meta-Analytic Modeling of Surrogate Endpoints in Cancer Screening Trials.Statistics in medicine · 2026Article
- Moving From Individualized Risk-Based Prevention to Benefit-Based Prevention: Estimating Individualized Life-Years Gained From Prevention Services as a Basis for Eligibility.Statistics in medicine · 2026Article
- Benefits and harms of lung cancer screening strategies in Argentina: a modeling study.Lancet regional health. Americas · 2026Article
- A DNA Methylation-based algorithm Improves Lung Cancer risk prediction in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial.Lung cancer (Amsterdam, Netherlands) · 2026Article
- East-West Disparities in Lung Cancer Screening: Subsolid Nodule Prevalence, Interval Growth, and Decision-Making Analysis.Diagnostics (Basel, Switzerland) · 2026Review
- Personalizing lung cancer screening recommendations for heterogeneous populations: a microsimulation study.Journal of the National Cancer Institute · 2026Article
- Understanding East-West differences in subsolid nodules: prevalence and overdiagnosis implications in lung cancer screening.Annals of medicine · 2025Article
- The lung cancer screening marathon after baseline: evidence from incidence nodules.European radiology · 2025Article
- An Everyday Patient-Centered Discussion Model for Primary Care: Protocol for a Feasibility and Acceptability Study of the Zeroing in on Individualized, Patient-Centered Decisions (ZIP) Approach.JMIR research protocols · 2025Article
- Article
- Natural history models for lung Cancer: A scoping review.Lung cancer (Amsterdam, Netherlands) · 2025Article
- Impact of Comorbidities on the Mortality Benefits of Lung Cancer Screening: A Post-Hoc Analysis of the PLCO and NLST Trials.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2025Article
- A Novel Automated Algorithm to Identify Lung Cancer Screening from Free Text of Radiology Orders.Journal of general internal medicine · 2025Article
9 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Background: Many health systems are exploring how to implement low-dose computed tomography (LDCT) screening programs that are effective and patient-centered. Objective: To examine factors that influence when LDCT screening is preference-sensitive. Design: State-transition microsimulation model. Data Sources: Two large randomized trials, published decision analyses, and the SEER (Surveillance, Epidemiology, and End Results) cancer registry. Target Population: U.S.-representative sample of simulated patients meeting current U.S. Preventive Services Task Force criteria for screening eligibility. Time Horizon: Lifetime. Perspective: Individual. Intervention: LDCT screening annually for 3 years. Outcome Measures: Lifetime quality-adjusted life-year gains and reduction in lung cancer mortality. To examine the effect of preferences on net benefit, disutilities (the "degree of dislike") quantifying the burden of screening and follow-up were varied across a likely range. The effect of varying the rate of false-positive screening results and overdiagnosis associated with screening was also examined. Results of Base-Case Analysis: Moderate differences in preferences about the downsides of LDCT screening influenced whether screening was appropriate for eligible persons with annual lung cancer risk less than 0.3% or life expectancy less than 10.5 years. For higher-risk eligible persons with longer life expectancy (roughly 50% of the study population), the benefits of LDCT screening overcame even highly negative views about screening and its downsides. Results of Sensitivity Analysis: Rates of false-positive findings and overdiagnosed lung cancer were not highly influential. Limitation: The quantitative thresholds that were identified may vary depending on the structure of the microsimulation model. Conclusion: Identifying circumstances in which LDCT screening is more versus less preference-sensitive may help clinicians personalize their screening discussions, tailoring to both preferences and clinical benefit. Primary Funding Source: None.
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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.