| Content Provider |
World Health Organization (WHO)-Global Index Medicus |
| Author |
Soghrati, Kam Stewart, Lori Bhatia, Rick Mayo, John R. Burrowes, Paul Johnston, Michael R. Roberts, Heidi Puksa, Serge Maceachern, Paul English, John Lam, Stephen Goss, Glenwood D. Tsai, Scott Atkar-khattra, Sukhinder Gingras, Michel Seely, Jean M. Martel, Simon Evans, Ken Amjadi, Kayvan Tammemagi, Martin C. Yee, John Manos, Daria Nicholas, Garth Finley, Richard Tremblay, Alain Liu, Geoffrey Mcwilliams, Annette Goffin, John Laberge, Francis Tsao, Ming-sound Yasufuku, Kazuhiro Nasute, Paola Berg, Christine D. |
| Description |
Author Affiliation: McWilliams A ( Vancouver General Hospital, Vancouver, BC, Canada.) |
| Abstract |
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.). |
| ISSN |
00284793 |
| e-ISSN |
15334406 |
| Journal |
New England Journal of Medicine |
| Issue Number |
10 |
| Volume Number |
369 |
| Language |
English |
| Publisher |
Massachusetts Medical Society (United States) |
| Publisher Date |
2013-09-05 |
| Publisher Place |
United States |
| Access Restriction |
Open |
| Subject Keyword |
Lung Neoplasms Pathology Lung Solitary Pulmonary Nodule Evidence-Based Medicine Follow-Up Studies Logistic Models Models, Statistical Multiple Pulmonary Nodules Probability Prospective Studies Tomography, X-Ray Computed Clinical Trial Multicenter Study Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Validation Studies Medicine |
| Content Type |
Text |
| Resource Type |
Article |
| Subject |
Medicine |
