ArticleCancer2014
Comparative analysis of 5 lung cancer natural history and screening models that reproduce outcomes of the NLST and PLCO trials.
Article in Cancer, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 3 of them syntheses that pooled it.
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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.
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Who cites it
56 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Screening for lung cancer: A systematic review of overdiagnosis and its implications.Molecular oncology · 2026Pooled it
- Guideline
- Guideline
- Lung cancer detectability by test, histology, stage, and gender: estimates from the NLST and the PLCO trials.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2015Trial
- Discrete-Event Simulation Modeling Framework for Cancer Interventions and Population Health in R (DESCIPHR): An Open-Source Pipeline.PharmacoEconomics · 2026Article
- Development and validation of a histology-specific natural history model of ovarian cancer.American journal of obstetrics and gynecology · 2025Article
- Stage- and histology-specific sensitivity for the detection of lung cancer of the NELSON screening protocol-A modeling study.International journal of cancer · 2025Article
- A Scoping Review on Calibration Methods for Cancer Simulation Models.Medical decision making : an international journal of the Society for Medical Decision Making · 2025Article
- Computed Tomographic Screening Intervals for Patients at Moderate Risk of Lung Cancer.JAMA network open · 2025Article
- Natural history models for lung Cancer: A scoping review.Lung cancer (Amsterdam, Netherlands) · 2025Article
- Benchmarking lung cancer screening programmes with adaptive screening frequency against the optimal screening schedules derived from the ENGAGE framework: a comparative microsimulation study.EClinicalMedicine · 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
- Lung cancer screening: where do we stand?Breathe (Sheffield, England) · 2024Review
- The Benefits and Harms of Lung Cancer Screening in Individuals With Comorbidities.JTO clinical and research reports · 2024Article
- Estimated US Cancer Deaths Prevented With Increased Use of Lung, Colorectal, Breast, and Cervical Cancer Screening.JAMA network open · 2023Article
- Birth Cohort‒Specific Smoking Patterns by Family Income in the U.S.American journal of preventive medicine · 2023Article
- Using the Past to Understand the Future of U.S. and Global Smoking Disparities: A Birth Cohort Perspective.American journal of preventive medicine · 2023Article
- The NCC mathematical modeling framework for decision-making of six major cancers.Journal of the National Cancer Center · 2023Article
- Risk Model-Based Lung Cancer Screening : A Cost-Effectiveness Analysis.Annals of internal medicine · 2023Article
- Optimizing the use of adjuvant chemotherapy in non-small cell lung cancer patients with comorbidities.Current problems in cancer · 2022Article
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
backgroundThe National Lung Screening Trial (NLST) demonstrated that low-dose computed tomography screening is an effective way of reducing lung cancer (LC) mortality. However, optimal screening strategies have not been determined to date and it is uncertain whether lighter smokers than those examined in the NLST may also benefit from screening. To address these questions, it is necessary to first develop LC natural history models that can reproduce NLST outcomes and simulate screening programs at the population level.
methodsFive independent LC screening models were developed using common inputs and calibration targets derived from the NLST and the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO). Imputation of missing information regarding smoking, histology, and stage of disease for a small percentage of individuals and diagnosed LCs in both trials was performed. Models were calibrated to LC incidence, mortality, or both outcomes simultaneously.
resultsInitially, all models were calibrated to the NLST and validated against PLCO. Models were found to validate well against individuals in PLCO who would have been eligible for the NLST. However, all models required further calibration to PLCO to adequately capture LC outcomes in PLCO never-smokers and light smokers. Final versions of all models produced incidence and mortality outcomes in the presence and absence of screening that were consistent with both trials.
conclusionsThe authors developed 5 distinct LC screening simulation models based on the evidence in the NLST and PLCO. The results of their analyses demonstrated that the NLST and PLCO have produced consistent results. The resulting models can be important tools to generate additional evidence to determine the effectiveness of lung cancer screening strategies using low-dose computed tomography.
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