ArticleCancer2011
Modeling the mortality reduction due to computed tomography screening for lung cancer.
Article in Cancer, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers, 1 of them a synthesis 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Lung cancer screening.Journal of the National Comprehensive Cancer Network : JNCCN · 2012Guideline
- Occult metastases and survival of lung cancer by clinical diagnosis and CT screening: A simulation study.PloS one · 2025Article
- Radiomics and artificial intelligence in lung cancer screening.Translational lung cancer research · 2021Review
- The Regimen of Computed Tomography Screening for Lung Cancer: Lessons Learned Over 25 Years From the International Early Lung Cancer Action Program.Journal of thoracic imaging · 2021Article
- Association of Smoking with Metabolic Volatile Organic Compounds in Exhaled Breath.International journal of molecular sciences · 2017Article
- The importance of the regimen of screening in maximizing the benefit and minimizing the harms.Annals of translational medicine · 2016Review
- Risk factors assessment and risk prediction models in lung cancer screening candidates.Annals of translational medicine · 2016Review
- Lung cancer screening guidelines: common ground and differences.Translational lung cancer research · 2014Review
- Article
- Screening for lung cancer with low-dose computed tomography: a review of current status.Journal of thoracic disease · 2013Review
- Cost-effectiveness of computed tomography screening for lung cancer in the United States.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2011Article
- Can imaging help improve the survival of cancer patients?Cancer imaging : the official publication of the International Cancer Imaging Society · 2011Review
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
Abstract
backgroundThe efficacy of computed tomography (CT) screening for lung cancer remains controversial because results from the National Lung Screening Trial are not yet available. In this study, the authors used data from a single-arm CT screening trial to estimate the mortality reduction using a modeling-based approach to construct a control comparison arm.
methodsTo estimate the potential lung cancer mortality reduction because of CT screening, a previously developed and validated model was applied to the screening trial to predict the number of lung cancer deaths in the absence of screening. By using age, gender, and smoking characteristics matching those of the trial participants, the model was used to simulate 5000 trials in the absence of CT screening to produce the expected number of lung cancer deaths along with 95% confidence intervals (95% CIs), while adjusting for healthy volunteer bias.
resultsThere were 64 observed lung cancer deaths in the screening cohort (n = 7995), whereas the model predicted 117.7 deaths (95% CI, 98 deaths-139 deaths), indicating a mortality reduction of 45.6% (P < .001). When a more conservative healthy volunteer adjustment was applied, 111.3 lung cancer deaths were predicted (95% CI, 91 deaths-132 deaths), for a lung cancer-specific mortality reduction of 42.5% (P < .001).
conclusionsThe results of the current study indicate that CT screening along with early stage treatment can reduce lung cancer-specific mortality. This mortality reduction is greatly influenced by the protocol of nodule follow-up and treatment, and the length of follow-up.
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