2 resultados para Emission Computed-tomography

em Brock University, Canada


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Background: Lung cancer (LC) is the leading cause of cancer death in the developed world. Most cancers are associated with tobacco smoking. A primary hope for reducing lung cancer has been prevention of smoking and successful smoking cessation programs. To date, these programs have not been as successful as anticipated. Objective: The aim of the current study was to evaluate whether lung cancer screening combining low dose computed tomography with autofluorescence bronchoscopy (combined CT & AFB) is superior to CT or AFB screening alone in improving lung cancer specific survival. In addition, the extent of improvement and ideal conditions for combined CT & AFB screening were evaluated. Methods: We applied decision analysis and Monte Carlo simulation modeling using TreeAge Software to evaluate our study aims. Histology- and stage specific probabilities of lung cancer 5-year survival proportions were taken from Surveillance and Epidemiologic End Results (SEER) Registry data. Screeningassociated data was taken from the US NCI Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO), National Lung Screening Trial (NLST), and US NCI Lung Screening Study (LSS), other relevant published data and expert opinion. Results: Decision Analysis - Combined CT and AFB was the best approach at Improving 5-year survival (Overall Expected Survival (OES) in the entire screened population was 0.9863) and in lung cancer patients only (Lung Cancer Specific Expected Survival (LOSES) was 0.3256). Combined screening was slightly better than CT screening alone (OES = 0.9859; LCSES = 0.2966), and substantially better than AFB screening alone (OES = 0.9842; LCSES = 0.2124), which was considerably better than no screening (OES = 0.9829; LCSES = 0.1445). Monte Carlo simulation modeling revealed that expected survival in the screened population and lung cancer patients is highest when screened using CT and combined CT and AFB. CT alone and combined screening was substantially better than AFB screening alone or no screening. For LCSES, combined CT and AFB screening is significantly better than CT alone (0.3126 vs. 0.2938, p< 0.0001). Conclusions: Overall, these analyses suggest that combined CT and AFB is slightly better than CT alone at improving lung cancer survival, and both approaches are substantially better than AFB screening alone or no screening.

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This thesis describes an ancillary project to the Early Diagnosis of Mesothelioma and Lung Cancer in Prior Asbestos Workers study and was conducted to determine the effects of asbestos exposure, pulmonary function and cigarette smoking in the prediction of pulmonary fibrosis. 613 workers who were occupationally exposed to asbestos for an average of 25.9 (SD=14.69) years were sampled from Sarnia, Ontario. A structured questionnaire was administered during a face-to-face interview along with a low-dose computed tomography (LDCT) of the thorax. Of them, 65 workers (10.7%, 95%CI 8.12—12.24) had LDCT-detected pulmonary fibrosis. The model predicting fibrosis included the variables age, smoking (dichotomized), post FVC % splines and post- FEV1% splines. This model had a receiver operator characteristic area under the curve of 0.738. The calibration of the model was evaluated with R statistical program and the bootstrap optimism-corrected calibration slope was 0.692. Thus, our model demonstrated moderate predictive performance.