The DOI matches its Crossref record; 28 of the 29 references it cites were found in a registry or an index.
Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening
Open accessAbstract
BACKGROUND: The aggressive and heterogeneous nature of lung cancer has thwarted efforts to reduce mortality from this cancer through the use of screening. The advent of low-dose helical computed tomography (CT) altered the landscape of lung-cancer screening, with studies indicating that low-dose CT detects many tumors at early stages. The National Lung Screening Trial (NLST) was conducted to determine whether screening with low-dose CT could reduce mortality from lung cancer. METHODS: From August 2002 through April 2004, we enrolled 53,454 persons at high risk for lung cancer at 33 U.S. medical centers. Participants were randomly assigned to undergo three annual screenings with either low-dose CT (26,722 participants) or single-view posteroanterior chest radiography (26,732). Data were collected on cases of lung cancer and deaths from lung cancer that occurred through December 31, 2009. RESULTS: The rate of adherence to screening was more than 90%. The rate of positive screening tests was 24.2% with low-dose CT and 6.9% with radiography over all three rounds. A total of 96.4% of the positive screening results in the low-dose CT group and 94.5% in the radiography group were false positive results. The incidence of lung cancer was 645 cases per 100,000 person-years (1060 cancers) in the low-dose CT group, as compared with 572 cases per 100,000 person-years (941 cancers) in the radiography group (rate ratio, 1.13; 95% confidence interval [CI], 1.03 to 1.23). There were 247 deaths from lung cancer per 100,000 person-years in the low-dose CT group and 309 deaths per 100,000 person-years in the radiography group, representing a relative reduction in mortality from lung cancer with low-dose CT screening of 20.0% (95% CI, 6.8 to 26.7; P=0.004). The rate of death from any cause was reduced in the low-dose CT group, as compared with the radiography group, by 6.7% (95% CI, 1.2 to 13.6; P=0.02). CONCLUSIONS: Screening with the use of low-dose CT reduces mortality from lung cancer. (Funded by the National Cancer Institute; National Lung Screening Trial ClinicalTrials.gov number, NCT00047385.).
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“For example, low-dose CT was shown to be useful for lung cancer screening [51].”
From Convolutional neural networks: an overview and application in radiology (2018) · cites this paper as [51]
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“Risk prediction was robust across multiple clinical scenarios, including a primary prevention asymptomatic setting with non-gated chest CT (NLST)18, as well as dedicated ECG-gated cardiac CT in stable (PROMISE)19 and acute (ROMICAT-II)20 chest pain setting.”
From Deep convolutional neural networks to predict cardiovascular risk from computed tomography (2021) · cites this paper as [18]
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“The majority of FHS (100%)44, NLST (91%)18, PROMISE (77%)45, and ROMICAT-II (66%)46 participants were non-Hispanic whites.”
From Deep convolutional neural networks to predict cardiovascular risk from computed tomography (2021) · cites this paper as [18]
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In the citing paper
“In NLST18, the coronary calcium score was measured manually in 396 randomly selected participants using 3D Slicer (V4).”
From Deep convolutional neural networks to predict cardiovascular risk from computed tomography (2021) · cites this paper as [18]
Experimental — accuracy not yet measuredIn the citing paper
“including the National Lung Cancer Screening Trial (NLST), which has become a key public data resource for machine learning research.”
From Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions (2024) · cites this paper as [27]
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Metadata
- Authors
- The National Lung Screening Trial Research Team
- Affiliations
- National Cancer Institute (US)
- Corresponding author
- The National Lung Screening Trial Research Team
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 2011-08-04
- Volume
- 365
- Issue
- 5
- Pages
- 395-409
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- PMC
- PMC4356534
- OpenAlex
- W130099911
- Cited by
- 11,064
- References
- 29
- Citations by year
- 2026: 748 · 2025: 875 · 2024: 940 · 2023: 943 · 2022: 930 · 2021: 955 · 2020: 887 · 2019: 757 · 2018: 723 · 2017: 591 · 2016: 591 · 2015: 610 · 2014: 527 · 2013: 494 · 2012: 374
- FWCI
- 406.72
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- New England Journal of Medicine (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (n01cn025516-044, n01cn025515-047, n01cn025513-043, n02cn63300-11-0-5, 1ul1rr033176-01, n01cn025514-038, n01cn025511-041, n01cn025524-036, n01cn075022-017, n01cn025476-008, n01cn025522-043, n01cn025512-050, UL1TR000124, n01cn025518-039, 3u10ca079778-14s1)
- National Cancer Institute (U01CA079778, N01 CN25514, N01 CN025511, N02-CN-63300, N01-CN-25 522, N01 CN-25524, N01-CN-25 476, N01 CN25515, U10CA080098, U01-CA-80098, N01 CN025516, U01 CA79778, N01 CN025515, N01 CN025514, U01CA080098, N01CN25511, N02 CN063300, N01 CN025522, U10 CA079778, N01 CN025476, N01CN75022, N01 CN025518, N01 CN025512, N01 CN025513, N01 CN075022, N01-CN-25513, N01 CN025524, N01 CN25512, N01CN25518, N01-CN-25 516)
- National Center for Research Resources (UL1-RR-033176)
- National Center for Advancing Translational Sciences
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
- Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Occupational and environmental lung diseases
- Keywords
- lung cancer screening, low-dose CT, lung cancer mortality, National Lung Screening Trial, chest radiography, screening adherence, false positives, lung cancer incidence, early cancer detection, high-risk individuals, cancer mortality reduction, lung cancer risk factors, smoking, chronic obstructive pulmonary disease, radon
- MeSH terms
- Aged, Female, Humans, Lung Neoplasms, Male, Middle Aged, Patient Compliance, Radiography, Thoracic, Tomography, X-Ray Computed, Bias, Incidence
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