The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Benefits and Harms of Computed Tomography Lung Cancer Screening Strategies: A Comparative Modeling Study for the U.S. Preventive Services Task Force
Open accessAbstract
BACKGROUND: The optimum screening policy for lung cancer is unknown. OBJECTIVE: To identify efficient computed tomography (CT) screening scenarios in which relatively more lung cancer deaths are averted for fewer CT screening examinations. DESIGN: Comparative modeling study using 5 independent models. DATA SOURCES: The National Lung Screening Trial; the Prostate, Lung, Colorectal, and Ovarian Cancer Screening trial; the Surveillance, Epidemiology, and End Results program; and the U.S. Smoking History Generator. TARGET POPULATION: U.S. cohort born in 1950. TIME HORIZON: Cohort followed from ages 45 to 90 years. PERSPECTIVE: Societal. INTERVENTION: 576 scenarios with varying eligibility criteria (age, pack-years of smoking, years since quitting) and screening intervals. OUTCOME MEASURES: Benefits included lung cancer deaths averted or life-years gained. Harms included CT examinations, false-positive results (including those obtained from biopsy/surgery), overdiagnosed cases, and radiation-related deaths. RESULTS OF BEST-CASE SCENARIO: The most advantageous strategy was annual screening from ages 55 through 80 years for ever-smokers with a smoking history of at least 30 pack-years and ex-smokers with less than 15 years since quitting. It would lead to 50% (model ranges, 45% to 54%) of cases of cancer being detected at an early stage (stage I/II), 575 screening examinations per lung cancer death averted, a 14% (range, 8.2% to 23.5%) reduction in lung cancer mortality, 497 lung cancer deaths averted, and 5250 life-years gained per the 100,000-member cohort. Harms would include 67,550 false-positive test results, 910 biopsies or surgeries for benign lesions, and 190 overdiagnosed cases of cancer (3.7% of all cases of lung cancer [model ranges, 1.4% to 8.3%]). RESULTS OF SENSITIVITY ANALYSIS: The number of cancer deaths averted for the scenario varied across models between 177 and 862; the number of overdiagnosed cases of cancer varied between 72 and 426. LIMITATIONS: Scenarios assumed 100% screening adherence. Data derived from trials with short duration were extrapolated to lifetime follow-up. CONCLUSION: Annual CT screening for lung cancer has a favorable benefit-harm ratio for individuals aged 55 through 80 years with 30 or more pack-years' exposure to smoking. PRIMARY FUNDING SOURCE: National Cancer Institute.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
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
Goldstraw, P., Crowley, J., Chansky, K., Giroux, D. J., Groome, P. A., Rami-Porta, R., Postmus, P. E., Rusch, V., & Sobin, L. (2007) · Journal of Thoracic Oncology · doi:10.1097/jto.0b013e31812f3c1a · Cited by 3,655
Cited by
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
Amann, A., Costello, B. D. L., Miekisch, W., Schubert, J., Buszewski, B., Pleil, J., Ratcliffe, N., & Risby, T. (2014) · Journal of Breath Research · doi:10.1088/1752-7155/8/3/034001 · Cited by 804
Knudsen, A. B., Zauber, A. G., Rutter, C. M., Naber, S. K., Doria-Rose, V. P., Pabiniak, C., Johanson, C., Fischer, S. E., Lansdorp-Vogelaar, I., & Kuntz, K. M. (2016) · JAMA · doi:10.1001/jama.2016.6828 · Cited by 474
Mazzone, P. J., Silvestri, G. A., Patel, S., Kanne, J. P., Kinsinger, L. S., Wiener, R. S., Soo Hoo, G., & Detterbeck, F. C. (2018) · Chest · doi:10.1016/j.chest.2018.01.016 · Cited by 348
(2017) · Radboud Repository (Radboud University) · Cited by 284
Metadata
- Authors
- de Koning, H. J., Meza, R., Plevritis, S. K., ten Haaf, K., Munshi, V. N., Jeon, J., Erdogan, S. A., Kong, C. Y., Han, S. S., van Rosmalen, J., Choi, S. E., Pinsky, P. F., de Gonzalez, A. B., Berg, C. D., Black, W. C., Tammemägi, M. C., Hazelton, W. D., Feuer, E. J., & McMahon, P. M.
- Venue
- Annals of Internal Medicine
- Publisher
- American College of Physicians
- Published
- 2014-03-04
- Volume
- 160
- Issue
- 5
- Pages
- 311-320
- ISSN
- 0003-4819 (ISSN-L)
- 1539-3704
- OpenAlex
- W2161254570
- Cited by
- 466
- References
- 2
- FWCI
- 35.08
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Benefits and Harms of Computed Tomography Lung Cancer Screening Strategies: A Comparative Modeling Study for the U.S. Preventive Services Task Force. https://app.cochat.ai/papers/10.7326/m13-2316
- The paper
- de Koning, H. J., Meza, R., Plevritis, S. K., ten Haaf, K., Munshi, V. N., Jeon, J., Erdogan, S. A., Kong, C. Y., Han, S. S., van Rosmalen, J., Choi, S. E., Pinsky, P. F., de Gonzalez, A. B., Berg, C. D., Black, W. C., Tammemägi, M. C., Hazelton, W. D., Feuer, E. J., & McMahon, P. M. (2014). Benefits and Harms of Computed Tomography Lung Cancer Screening Strategies: A Comparative Modeling Study for the U.S. Preventive Services Task Force. Annals of Internal Medicine. https://doi.org/10.7326/m13-2316
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.