ArticleInternational journal of cancer2017
The impact of overdiagnosis on the selection of efficient lung cancer screening strategies.
Article in International journal of cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03394703 (Korean Lung Cancer Screening Project for High-risk Smokers to Evaluate Effectiveness and Feasibility of Lung Cancer Screening With Low-dose Computed Tomography for Implementing National Cancer Screening Program), which is not on this map. Cited by 26 papers, 3 of them syntheses that pooled it.
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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.
Korean Lung Cancer Screening Project for High-risk Smokers to Evaluate Effectiveness and Feasibility of Lung Cancer Screening With Low-dose Computed Tomography for Implementing National Cancer Screening Program
Who cites it
26 citing papers in PubMed, 3 syntheses or guidelines pooled it, 44 citations in OpenAlex.
- Pooled it
- 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
- Lung Cancer Screening, Version 3.2018, NCCN Clinical Practice Guidelines in Oncology.Journal of the National Comprehensive Cancer Network : JNCCN · 2018Guideline
- Stage- and histology-specific sensitivity for the detection of lung cancer of the NELSON screening protocol-A modeling study.International journal of cancer · 2025Article
- Structured narrative review on lung cancer screening: current evidence, clinical practice implications and implementation insights from a multidisciplinary task force and patient representatives.European respiratory review : an official journal of the European Respiratory Society · 2025Review
- Screening and novel diagnostic technologies for melanoma: an update.Melanoma management · 2025Review
- Natural history models for lung Cancer: A scoping review.Lung cancer (Amsterdam, Netherlands) · 2025Article
- Survival of lung cancer patients according to screening eligibility using Korean Lung Cancer Registry 2014-2016.Scientific reports · 2024Article
- The Impact of Model Assumptions on Personalized Lung Cancer Screening Recommendations.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Article
- Using the Past to Understand the Future of U.S. and Global Smoking Disparities: A Birth Cohort Perspective.American journal of preventive medicine · 2023Article
- Birth Cohort‒Specific Smoking Patterns by Family Income in the U.S.American journal of preventive medicine · 2023Article
- Selection of eligible participants for screening for lung cancer using primary care data.Thorax · 2022Article
- Personalising lung cancer screening: An overview of risk-stratification opportunities and challenges.International journal of cancer · 2021Review
- Patient motivations for non-adherence to lung cancer screening in a military population.Journal of thoracic disease · 2020Article
- Risk prediction models versus simplified selection criteria to determine eligibility for lung cancer screening: an analysis of German federal-wide survey and incidence data.European journal of epidemiology · 2020Article
- A Comparative Modeling Analysis of Risk-Based Lung Cancer Screening Strategies.Journal of the National Cancer Institute · 2020Article
- Optimizing selection of candidates for lung cancer screening: role of comorbidity, frailty and life expectancy.Translational lung cancer research · 2019Article
- Implementation planning for lung cancer screening in China.Precision clinical medicine · 2019Review
- Overdiagnosis in primary care: framing the problem and finding solutions.BMJ (Clinical research ed.) · 2018Review
- Identifying Patients for Whom Lung Cancer Screening Is Preference-Sensitive: A Microsimulation Study.Annals of internal medicine · 2018Article
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Authors and funding
13 authors at 8 institutions in 3 countries.
Funding
Abstract
The U.S. Preventive Services Task Force (USPSTF) recently updated their national lung screening guidelines and recommended low-dose computed tomography (LDCT) for lung cancer (LC) screening through age 80. However, the risk of overdiagnosis among older populations is a concern. Using four comparative models from the Cancer Intervention and Surveillance Modeling Network, we evaluate the overdiagnosis of the screening program recommended by USPSTF in the U.S. 1950 birth cohort. We estimate the number of LC deaths averted by screening (D) per overdiagnosed case (O), yielding the ratio D/O, to quantify the trade-off between the harms and benefits of LDCT. We analyze 576 hypothetical screening strategies that vary by age, smoking, and screening frequency and evaluate efficient screening strategies that maximize the D/O ratio and other metrics including D and life-years gained (LYG) per overdiagnosed case. The estimated D/O ratio for the USPSTF screening program is 2.85 (model range: 1.5-4.5) in the 1950 birth cohort, implying LDCT can prevent ∼3 LC deaths per overdiagnosed case. This D/O ratio increases by 22% when the program stops screening at an earlier age 75 instead of 80. Efficiency frontier analysis shows that while the most efficient screening strategies that maximize the mortality reduction (D) irrespective of overdiagnosis screen through age 80, screening strategies that stop at age 75 versus 80 produce greater efficiency in increasing life-years gained per overdiagnosed case. Given the risk of overdiagnosis with LC screening, the stopping age of screening merits further consideration when balancing benefits and harms.
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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.