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The Probability of Malignancy in Solitary Pulmonary Nodules: Application to Small Radiologically Indeterminate Nodules
Abstract
BACKGROUND: A clinical prediction model to identify malignant nodules based on clinical data and radiological characteristics of lung nodules was derived using logistic regression from a random sample of patients (n = 419) and tested on data from a separate group of patients (n = 210). OBJECTIVE: To use multivariate logistic regression to estimate the probability of malignancy in radiologically indeterminate solitary pulmonary nodules (SPNs) in a clinically relevant subset of patients with SPNs that measured between 4 and 30 mm in diameter. PATIENTS AND METHODS: A retrospective cohort study at a multispecialty group practice included 629 patients (320 men, 309 women) with newly discovered (between January 1, 1984, and May 1, 1986) 4- to 30-mm radiologically indeterminate SPNs on chest radiography. Patients with a diagnosis of cancer within 5 years prior to the discovery of the nodule were excluded. Clinical data included age, sex, cigarette-smoking status, and history of extrathoracic malignant neoplasm, asbestos exposure, and chronic interstitial or obstructive lung disease; chest radiological data included the diameter, location, edge characteristics (eg, lobulation, spiculation, and shagginess), and other characteristics (eg, cavitation) of the SPNs. Predictors were identified in a random sample of two thirds of the patients and tested in the remaining one third. RESULTS: Sixty-five percent of the nodules were benign, 23% were malignant, and 12% were indeterminate. Three clinical characteristics (age, cigarette-smoking status, and history of cancer [diagnosis, > or = 5 years ago]) and 3 radiological characteristics (diameter, spiculation, and upper lobe location of the SPNs) were independent predictors of malignancy. The area (+/-SE) under the evaluated receiver operating characteristic curve was 0.8328 +/- 0.0226. CONCLUSION: Three clinical and 3 radiographic characteristics predicted the malignancy in radiologically indeterminate SPNs.
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A REVIEW OF GOODNESS OF FIT STATISTICS FOR USE IN THE DEVELOPMENT OF LOGISTIC REGRESSION MODELS1
LEMESHOW, S., & HOSMER, D. W. (1982) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a113284 · Cited by 1,947
Clinical Prediction Rules: Applications and Methodological Standards
Wasson, J. H., Sox, H. C., Neff, R. K., & Goldman, L. (1985) · New England Journal of Medicine · doi:10.1056/nejm198509263131306 · Cited by 1,357
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Gould, M. K., Donington, J., Lynch, W. R., Mazzone, P. J., Midthun, D. E., Naidich, D. P., & Wiener, R. S. (2013) · Chest · doi:10.1378/chest.12-2351 · Cited by 1,450
Fihn, S. D., Gardin, J. M., Abrams, J., Berra, K., Blankenship, J. C., Dallas, A. P., Douglas, P. S., Foody, J. M., Gerber, T. C., Hinderliter, A. L., et al. (2012) · Circulation · doi:10.1161/cir.0b013e318277d6a0 · Cited by 845
Evaluation of Patients With Pulmonary Nodules: When Is It Lung Cancer?
Gould, M. K., Fletcher, J., Iannettoni, M. D., Lynch, W. R., Midthun, D. E., Naidich, D. P., & Ost, D. E. (2007) · Chest · doi:10.1378/chest.07-1353 · Cited by 503
Folch, E. E., Pritchett, M. A., Nead, M. A., Bowling, M. R., Murgu, S. D., Krimsky, W. S., Murillo, B. A., LeMense, G. P., Minnich, D. J., Bansal, S., et al. (2019) · Journal of Thoracic Oncology · doi:10.1016/j.jtho.2018.11.013 · Cited by 420
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
Metadata
- Authors
- Swensen, S. J.
- Venue
- Archives of Internal Medicine
- Publisher
- American Medical Association (AMA)
- Published
- 1997-04-28
- Volume
- 157
- Issue
- 8
- Pages
- 849
- ISSN
- 0003-9926 (ISSN-L)
- OpenAlex
- W2020089990
- Cited by
- 810
- References
- 2
- FWCI
- 7.73
- Type
- journal article
- Language
- en
- Open access
- closed
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- Swensen, S. J. (1997). The Probability of Malignancy in Solitary Pulmonary Nodules: Application to Small Radiologically Indeterminate Nodules. Archives of Internal Medicine. https://doi.org/10.1001/archinte.1997.00440290031002
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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