Overdiagnosis in Low-Dose Computed Tomography Screening for Lung Cancer
Open accessAbstract
IMPORTANCE: Screening for lung cancer has the potential to reduce mortality, but in addition to detecting aggressive tumors, screening will also detect indolent tumors that otherwise may not cause clinical symptoms. These overdiagnosis cases represent an important potential harm of screening because they incur additional cost, anxiety, and morbidity associated with cancer treatment. OBJECTIVE: To estimate overdiagnosis in the National Lung Screening Trial (NLST). DESIGN, SETTING, AND PARTICIPANTS: We used data from the NLST, a randomized trial comparing screening using low-dose computed tomography (LDCT) vs chest radiography (CXR) among 53 452 persons at high risk for lung cancer observed for 6.4 years, to estimate the excess number of lung cancers in the LDCT arm of the NLST compared with the CXR arm. MAIN OUTCOMES AND MEASURES: We calculated 2 measures of overdiagnosis: the probability that a lung cancer detected by screening with LDCT is an overdiagnosis (PS), defined as the excess lung cancers detected by LDCT divided by all lung cancers detected by screening in the LDCT arm; and the number of cases that were considered overdiagnosis relative to the number of persons needed to screen to prevent 1 death from lung cancer. RESULTS: During follow-up, 1089 lung cancers were reported in the LDCT arm and 969 in the CXR arm of the NLST. The probability is 18.5% (95% CI, 5.4%-30.6%) that any lung cancer detected by screening with LDCT was an overdiagnosis, 22.5% (95% CI, 9.7%-34.3%) that a non-small cell lung cancer detected by LDCT was an overdiagnosis, and 78.9% (95% CI, 62.2%-93.5%) that a bronchioalveolar lung cancer detected by LDCT was an overdiagnosis. The number of cases of overdiagnosis found among the 320 participants who would need to be screened in the NLST to prevent 1 death from lung cancer was 1.38. CONCLUSIONS AND RELEVANCE: More than 18% of all lung cancers detected by LDCT in the NLST seem to be indolent, and overdiagnosis should be considered when describing the risks of LDCT screening for lung cancer.
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The translation of mortality benefits from lung cancer screening to the general population has proven challenging given issues around false positives, overdiagnosis, and complication rates, while ensuring attendance and coverage given the prohibitive costs and infrastructure required.
“The translation of mortality benefits to the general population has proven challenging, however, given the well documented issues around false positives, overdiagnosis, and complication rates, while ensuring attendance and coverage given the prohibitive costs and infrastructure required.41”
From Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. (2024) · cites this paper as [41]
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Cites
Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening
The National Lung Screening Trial Research Team (2011) · New England Journal of Medicine · doi:10.1056/nejmoa1102873 · Cited by 11,064 · see citing works
Travis, W. D., Brambilla, E. M., Noguchi, M., Nicholson, A. G., Geisinger, K. R., Yatabe, Y., Beer, D. G., Powell, C. A., Riely, G. J., Schil, P. E. V., et al. (2011) · Journal of Thoracic Oncology · doi:10.1097/jto.0b013e318206a221 · Cited by 4,780 · see citing works
Self-citationWelch, H. G., & Black, W. C. (2010) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djq099 · Cited by 1,601 · see citing works
Self-citationEffect of Three Decades of Screening Mammography on Breast-Cancer Incidence
Bleyer, A., & Welch, H. G. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1206809 · Cited by 1,371 · see citing works
Benefits and Harms of CT Screening for Lung Cancer
Bach, P. B., Mirkin, J. N., Oliver, T. K., Azzoli, C. G., Berry, D. A., Brawley, O. W., Byers, T., Colditz, G. A., Gould, M. K., Jett, J. R., et al. (2012) · JAMA · doi:10.1001/jama.2012.5521 · Cited by 1,237 · see citing works
Patz, E. F., Goodman, P. C., & Bepler, G. (2000) · New England Journal of Medicine · doi:10.1056/nejm200011303432208 · Cited by 600 · see citing works
Self-citationLung Cancer Mortality in the Mayo Lung Project: Impact of Extended Follow-up
Marcus, P. M., Bergstralh, E. J., Fagerstrom, R. M., et al. (2000) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/92.16.1308 · Cited by 526 · see citing works
Sone, S., Li, F., Yang, Z.-G., et al. (2001) · British Journal of Cancer · doi:10.1054/bjoc.2000.1531 · Cited by 499 · see citing works
Fontana, R. S., SANDERSON, D. R., Taylor, W. F., Woolner, L. B., Miller, W. E., Muhm, J. R., & Uhlenhopp, M. A. (1984) · PubMed · doi:10.1164/arrd.1984.130.4.561 · Cited by 421 · see citing works
Screening for lung cancer. A critique of the mayo lung project
Fontana, R. S., SANDERSON, D. R., Woolner, L. B., et al. (1991) · Cancer · doi:10.1002/1097-0142(19910215)67:4+ · Cited by 391 · see citing works
Effect of Three Decades of Screening Mammography on Breast-Cancer Incidence
Bleyer, A., & Welch, H. G. (2013) · Obstetrical & Gynecological Survey · doi:10.1097/ogx.0b013e3182978e4a · Cited by 245 · see citing works
Extended Lung Cancer Incidence Follow-up in the Mayo Lung Project and Overdiagnosis
Marcus, P. M., Bergstralh, E. J., ZWEIG, M. H., et al. (2006) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djj207 · Cited by 231 · see citing works
Estimating Overdiagnosis in Low-Dose Computed Tomography Screening for Lung Cancer
Veronesi, G., Maisonneuve, P., Bellomi, M., Rampinelli, C., Durli, I., Bertolotti, R., & Spaggiari, L. (2012) · Annals of Internal Medicine · doi:10.7326/0003-4819-157-11-201212040-00005 · Cited by 160 · see citing works
Fontana, R. S., SANDERSON, D. R., Woolner, L. B., et al. (1975) · CHEST Journal · doi:10.1378/chest.67.5.511 · Cited by 124 · see citing works
Teraoka, S. N., Malone, K. E., Doody, D. R., Suter, N. M., Ostrander, E. A., Daling, J. R., & CONCANNON, P. J. (2001) · Cancer · doi:10.1002/1097-0142(20010801)92:3 · Cited by 111 · see citing works
5-Year Lung Cancer Screening Experience
Lindell, R. M., Hartman, T. E., Swensen, S. J., et al. (2009) · CHEST Journal · doi:10.1378/chest.09-0915 · Cited by 88 · see citing works
Dammas, S. (2001) · Lung Cancer · doi:10.1016/s0169-5002(01)00190-8 · Cited by 55 · see citing works
Necropsy Evidence of Detection Bias in the Diagnosis of Lung Cancer
McFarlane, M. J. (1986) · Archives of Internal Medicine · doi:10.1001/archinte.1986.00360210059009 · Cited by 34 · see citing works
Cancer, concepts, cohorts and complexity: avoiding oversimplification of overdiagnosis
Detterbeck, F. C. (2012) · Thorax · doi:10.1136/thoraxjnl-2012-201779 · Cited by 26 · see citing works
Lung Cancer Screening, Overdiagnosis Bias, and Reevaluation of the Mayo Lung Project
Patz, E. F. (2006) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djj226 · Cited by 20 · see citing works
Self-citationNg, B., Mbbs, & Franzcr (2015) · Cited by 13 · see citing works
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Cited by
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Bray, F., Laversanne, M., Sung, H., Ferlay, J., Siegel, R. L., Soerjomataram, I., & Jemal, A. (2024) · CA: a cancer journal for clinicians · doi:10.3322/caac.21834 · Cited by 27,064 · see citing works
Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial
de Koning, H. J., van der Aalst, C. M., de Jong, P. A., Scholten, E. T., Nackaerts, K., Heuvelmans, M. A., Lammers, J.-W. J., Weenink, C., Yousaf-Khan, U., Horeweg, N., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa1911793 · Cited by 3,624 · see citing works
Artificial intelligence in cancer imaging: Clinical challenges and applications
Bi, W. L., Hosny, A., Schabath, M. B., Giger, M. L., Birkbak, N. J., Mehrtash, A., Allison, T., Arnaout, O., Abbosh, C., Dunn, I. F., et al. (2019) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21552 · Cited by 1,846 · see citing works
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., et al. (2021) · The Lancet Regional Health - Europe · doi:10.1016/j.lanepe.2021.100179 · Cited by 230 · see citing works
Brims, F. J. H., Harris, E. J. A., Murray, C., Kumarasamy, C., Ho, A., Adler, B., Franklin, P., & de Klerk, N. H. (2023) · Respirology · doi:10.1111/resp.14487 · Cited by 16 · see citing works
- Authors
- Patz, E. F., Pinsky, P., Gatsonis, C., Sicks, J. D., Kramer, B. S., Tammemägi, M. C., Chiles, C., Black, W. C., & Aberle, D. R.
- Affiliations
- Duke University (US)
- National Cancer Institute (US)
- Brown University (US)
- Brock University (CA)
- Wake Forest University Health Sciences (US)
- Dartmouth College (US)
- University of California, Los Angeles (US)
- Corresponding author
- Patz, Edward F.
- ORCID
- Venue
- JAMA Internal Medicine
- Publisher
- American Medical Association (AMA)
- Published
- 2014-02-01
- Volume
- 174
- Issue
- 2
- Pages
- 269
- ISSN
- 2168-6106 (ISSN-L)
- PMC
- PMC4040004
- OpenAlex
- W2107692993
- Cited by
- 776
- References
- 21
- Citations by year
- 2026: 22 · 2025: 31 · 2024: 43 · 2023: 51 · 2022: 70 · 2021: 72 · 2020: 67 · 2019: 65 · 2018: 83 · 2017: 51 · 2016: 71 · 2015: 80 · 2014: 66 · 2013: 3
- FWCI
- 71.53
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- JAMA Internal Medicine (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (n01cn025516-044, n01cn025515-047, n01cn025513-043, n02cn63300-11-0-5, n01cn025514-038, n01cn025511-041, n01cn025524-036, n01cn075022-017, n01cn025476-008, n01cn025522-043, n01cn025512-050, n01cn025518-039)
- National Cancer Institute (U01CA079778, N01 CN25514, N01 CN025511, N02-CN-63300, N01-CN-25 522, N01 CN-25524, N01-CN-25 476, N01 CN25515, N01 CN025516, N01 CN025515, N01 CN025514, U01CA080098, N01CN25511, N02 CN063300, N01 CN025522, N01 CN025476, N01CN75022, N01 CN025518, N01 CN025512, N01 CN025513, N01 CN075022, N01-CN-25513, N01 CN025524, N01 CN25512, N01CN25518, N01-CN-25 516)
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
- Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
- Health Sciences › Health Professions › General Health Professions › Healthcare cost, quality, practices
- Keywords
- overdiagnosis, lung cancer screening, low-dose CT, National Lung Screening Trial, chest radiography, indolent tumors, non-small cell lung cancer, bronchioloalveolar carcinoma, screening harms
- MeSH terms
- Aged, Carcinoma, Non-Small-Cell Lung, Diagnosis, Differential, Diagnostic Errors, Dose-Response Relationship, Radiation, Female, Follow-Up Studies, Humans, Lung Neoplasms, Male, Mass Screening, Middle Aged, Probability, Prospective Studies, Time Factors, Tomography, X-Ray Computed, United States, Reproducibility of Results, Survival Rate
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