Lung cancer mortality reduction by LDCT screening: UKLS randomised trial results and international meta-analysis
Open accessAbstract
BACKGROUND: The NLST reported a significant 20% reduction in lung cancer mortality with three annual low-dose CT (LDCT) screens and the Dutch-Belgian NELSON trial indicates a similar reduction. We present the results of the UKLS trial. METHODS: From October 2011 to February 2013, we randomly allocated 4 055 participants to either a single invitation to screening with LDCT or to no screening (usual care). Eligible participants (aged 50-75) had a risk score (LLPv2) ≥ 4.5% of developing lung cancer over five years. Data were collected on lung cancer cases to 31 December 2019 and deaths to 29 February 2020 through linkage to national registries. The primary outcome was mortality due to lung cancer. We included our results in a random-effects meta-analysis to provide a synthesis of the latest randomised trial evidence. FINDINGS: 1 987 participants in the intervention and 1 981 in the usual care arms were followed for a median of 7.3 years (IQR 7.1-7.6), 86 cancers were diagnosed in the LDCT arm and 75 in the control arm. 30 lung cancer deaths were reported in the screening arm, 46 in the control arm, (relative rate 0.65 [95% CI 0.41-1.02]; p=0.062). The meta-analysis indicated a significant reduction in lung cancer mortality with a pooled overall relative rate of 0.84 (95% CI 0.76-0.92) from nine eligible trials. INTERPRETATION: The UKLS trial of single LDCT indicates a reduction of lung cancer death of similar magnitude to the NELSON and NLST trials and was included in a meta-analysis of nine randomised trials which provides unequivocal support for lung cancer screening in identified risk groups. FUNDING: NIHR Health Technology Assessment programme; NIHR Policy Research programme; Roy Castle Lung Cancer Foundation.
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The National Lung Cancer Screening Trial has become a key public data resource for machine learning research.
“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 [28]
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- Authors
- Field, J. K., Vulkan, D., Davies, M. P. A., Baldwin, D. R., Brain, K. E., Devaraj, A., Eisen, T., Gosney, J., Green, B. A., Holemans, J. A., Kavanagh, T., Kerr, K. M., Ledson, M., Lifford, K. J., McRonald, F. E., Nair, A., Page, R. D., Parmar, M. K. B., Rassl, D. M., Rintoul, R. C., Screaton, N. J., Wald, N. J., Weller, D., Whynes, D. K., Williamson, P. R., Yadegarfar, G., Gabe, R., & Duffy, S. W.
- Affiliations
- University of Liverpool (GB)
- Queen Mary University of London (GB)
- Nottingham University Hospitals NHS Trust (GB)
- Cardiff University (GB)
- Royal Brompton Hospital (GB)
- University of Cambridge (GB)
- Liverpool University Hospitals NHS Foundation Trust (GB)
- Liverpool Heart and Chest Hospital (GB)
- Aberdeen Royal Infirmary (GB)
- Royal London Hospital (GB)
- MRC Clinical Trials Unit at UCL (GB)
- Royal Papworth Hospital (GB)
- Papworth Hospital NHS Foundation Trust (GB)
- University College London (GB)
- University of Edinburgh (GB)
- University of Nottingham (GB)
- Corresponding author
- Field, John K.
- ORCID
- Venue
- The Lancet Regional Health - Europe
- Publisher
- Elsevier BV
- Published
- 2021-11
- Volume
- 10
- Pages
- 100179
- ISSN
- 2666-7762 (ISSN-L)
- PMC
- PMC8589726
- OpenAlex
- W3199475400
- Cited by
- 230
- References
- 47
- Citations by year
- 2026: 31 · 2025: 56 · 2024: 56 · 2023: 50 · 2022: 32 · 2021: 5
- FWCI
- 23.21
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- The Lancet Regional Health - Europe (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- ORCA Online Research @Cardiff (Cardiff University) (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Queen Mary Research Online (Queen Mary University of London) (submittedVersion, cc-by-nc-nd)
- Funders
- Roy Castle Lung Cancer Foundation
- National Institute for Health Research (PR-PRU-1217-21601)
- Health Technology Assessment Programme
- NIHR Cambridge Biomedical Research Centre
- Public Health England
- 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, NELSON trial
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