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Probability of Cancer in Pulmonary Nodules Detected on First Screening CT
Open accessAbstract
BACKGROUND: Major issues in the implementation of screening for lung cancer by means of low-dose computed tomography (CT) are the definition of a positive result and the management of lung nodules detected on the scans. We conducted a population-based prospective study to determine factors predicting the probability that lung nodules detected on the first screening low-dose CT scans are malignant or will be found to be malignant on follow-up. METHODS: We analyzed data from two cohorts of participants undergoing low-dose CT screening. The development data set included participants in the Pan-Canadian Early Detection of Lung Cancer Study (PanCan). The validation data set included participants involved in chemoprevention trials at the British Columbia Cancer Agency (BCCA), sponsored by the U.S. National Cancer Institute. The final outcomes of all nodules of any size that were detected on baseline low-dose CT scans were tracked. Parsimonious and fuller multivariable logistic-regression models were prepared to estimate the probability of lung cancer. RESULTS: In the PanCan data set, 1871 persons had 7008 nodules, of which 102 were malignant, and in the BCCA data set, 1090 persons had 5021 nodules, of which 42 were malignant. Among persons with nodules, the rates of cancer in the two data sets were 5.5% and 3.7%, respectively. Predictors of cancer in the model included older age, female sex, family history of lung cancer, emphysema, larger nodule size, location of the nodule in the upper lobe, part-solid nodule type, lower nodule count, and spiculation. Our final parsimonious and full models showed excellent discrimination and calibration, with areas under the receiver-operating-characteristic curve of more than 0.90, even for nodules that were 10 mm or smaller in the validation set. CONCLUSIONS: Predictive tools based on patient and nodule characteristics can be used to accurately estimate the probability that lung nodules detected on baseline screening low-dose CT scans are malignant. (Funded by the Terry Fox Research Institute and others; ClinicalTrials.gov number, NCT00751660.).
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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
Cited by
MacMahon, H., Naidich, D. P., Goo, J. M., Lee, K. S., Leung, A. N. C., Mayo, J. R., Mehta, A. C., Ohno, Y., Powell, C. A., Prokop, M., et al. (2017) · Radiology · doi:10.1148/radiol.2017161659 · Cited by 2,491
Self-citationEuropean position statement on lung cancer screening
Oudkerk, M., Devaraj, A., Vliegenthart, R., Henzler, T., Prosch, H., Heussel, C. P., Bastarrika, G., Sverzellati, N., Mascalchi, M., Delorme, S., et al. (2017) · The Lancet Oncology · doi:10.1016/s1470-2045(17)30861-6 · Cited by 587
Adams, S. J., Stone, E., Baldwin, D. R., Vliegenthart, R., Lee, P., & Fintelmann, F. J. (2023) · The Lancet · doi:10.1016/s0140-6736(22)01694-4 · Cited by 467
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
Huang, S., Yang, J., Shen, N., Xu, Q., & Zhao, Q. (2023) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2023.01.006 · Cited by 317
Metadata
- Authors
- McWilliams, A., Tammemagi, M. C., Mayo, J. R., Roberts, H., Liu, G., Soghrati, K., Yasufuku, K., Martel, S., Laberge, F., Gingras, M., Atkar-Khattra, S., Berg, C. D., Evans, K., Finley, R., Yee, J., English, J., Nasute, P., Goffin, J., Puksa, S., Stewart, L., Tsai, S., Johnston, M. R., Manos, D., Nicholas, G., Goss, G. D., Seely, J. M., Amjadi, K., Tremblay, A., Burrowes, P., MacEachern, P., Bhatia, R., Tsao, M.-S., & Lam, S.
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 2013-09-05
- Volume
- 369
- Issue
- 10
- Pages
- 910-919
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- OpenAlex
- W2114175038
- Cited by
- 1,414
- References
- 1
- FWCI
- 52.13
- Type
- journal article
- Language
- en
- Open access
- bronze
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- McWilliams, A., Tammemagi, M. C., Mayo, J. R., Roberts, H., Liu, G., Soghrati, K., Yasufuku, K., Martel, S., Laberge, F., Gingras, M., Atkar-Khattra, S., Berg, C. D., Evans, K., Finley, R., Yee, J., English, J., Nasute, P., Goffin, J., Puksa, S., . . . Lam, S. (2013). Probability of Cancer in Pulmonary Nodules Detected on First Screening CT. New England Journal of Medicine. https://doi.org/10.1056/nejmoa1214726
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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.