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A. McWilliams



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    O06 - Cancer Control and Epidemiology I (ID 135)

    • Event: WCLC 2013
    • Type: Oral Abstract Session
    • Track: Prevention & Epidemiology
    • Presentations: 1
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      O06.06 - Factors Associated with Smoking Cessation in Participants of The Pan Canadian Early Lung Cancer Study (ID 1469)

      11:35 - 11:45  |  Author(s): A. McWilliams

      • Abstract
      • Presentation
      • Slides

      Background
      Lung cancer screening programs provide unique opportunities to facilitate smoking cessation in smokers who participate in these programs. However, the effects of screening on motivation to quit might be mediated or modified by other variables. Identifying the participants more likely to quit will allow rapid application of smoking cessation resources to these participants, while those least likely to quit can be afforded experimental interventions. The aim of our study was to assess the impact of lung cancer screening on smoking cessation in current smokers at the time of enrollment and to identify factors that were associated with quitting smoking in this screening population.

      Methods
      Using data collected from the Pan-Canadian Study of Early Detection of Lung Cancer, both univariate and multivariable logistic regression analysis was used to identify predictors of smoking cessation among current smokers at enrolment. Smoking cessation was defined as quitting for at least a 6 month period, occurring anytime after enrolment.

      Results
      We analyzed baseline and follow-up questionnaires of 2320 participants, of which 1419 were current smokers. Of these 1419 patients, 392 (27.8%) met the definition of smoking cessation during a median of two annual follow-up visits. In both univariate and multivariable (MV) analysis, greater smoking cessation was associated with four factors: (i) having a diagnosis of lung cancer at any time during the screening process, with a MV Odds ratio (OR) of quitting of 2.4 (95%CI: 1.1-5.0); (ii) lower and medium nicotine addiction as assessed by the Fagerström Nicotine Dependence Scale Score, with MV-ORs of 3.2 (95%CI: 2.2-4.6) and 1.4 (95%CI: 0.9-2.0), respectively; (iii) having higher education, with MV-OR: 1.4 (95%CI: 1.1-1.9); and (iv) having an earlier age of onset of regular alcohol intake, with MV-OR of 1.11 (95%CI: 1.02-1.21) per 5 year decrease in age. Smoking cessation was also associated with (i) previous attempts of quitting [UV-OR 1.8 (95%CI: 1.2-2.7)], willingness to quit smoking within the next month (at baseline screening) [UV-OR 2.2 (95%CI: 1.8-2.9)] or within the next 6 months after baseline screening [UV-OR 1.8 (95%CI: 1.3.-2.4)]. Second-hand smoking exposure, including exposure as a child, or as an adult at work, at home, privately with friends, or in public settings, or a cumulative index of these different exposures, was not associated with smoking cessation. Presence of potential index symptoms for lung disease, including shortness of breath, cough (both dry and productive), hoarseness, audible wheezing or even chest pain, was not associated with an increased chance of smoking cessation.

      Conclusion
      The diagnosis of a new lung cancer had a major positive impact on screening participants quitting smoking, as were factors such as lower nicotine dependence, higher education, earlier starting alcohol drinking age, and willingness to quit. Whether a new lung cancer diagnosis triggered additional efforts by clinicians to help the person quit will be explored further. Individual lung symptoms and secondhand smoke exposure were not associated with smoking cessation. (Geoffrey Liu and Martin Tamemmagi are co-senior authors)

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    P2.20 - Poster Session 2 - Early Detection and Screening (ID 173)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Imaging, Staging & Screening
    • Presentations: 1
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      P2.20-010 - Raman Spectroscopy Based Breath Analysis with Potential for Lung Cancer Detection (ID 3395)

      09:30 - 09:30  |  Author(s): A. McWilliams

      • Abstract

      Background
      Lung cancer is the top cancer killer in North America and worldwide. Current lung cancer detection tools involving X-ray, CT and bronchoscopy are relatively time-consuming and costly. Breath analyses done by mass spectrometry have shown that certain endogenous volatile organic compounds (VOCs) are related to lung cancer and revealed the potential of breath analysis for lung cancer detection. But mass spectrometry is costly and has slow turnaround times. In another interesting development, electronic noses were made for breath analysis, however the signals generated from semiconductor array cannot accurately quantify nor correlate with VOCs. Raman spectroscopy is a promising candidate for breath analysis because it can offer unique fingerprint-type signals for molecular identification. Our objective is to develop a simple, cost-effective and non-invasive tool based on Raman spectroscopy for breath analysis and potentially for lung cancer screening.

      Methods
      A Raman-gas analyzer was designed and built, based on photonic technologies. We employed a hollow core-photonic crystal fibre (HC-PCF), a novel light guide that allows light to be guided in a small hollow core and it can be filled with a gaseous sample (i.e., human breath) for spectral analysis. A gas supply system was built to provide a sealed environment for the loading and unloading of gaseous samples. A 785 nm diode laser was used for Raman excitation. Stokes Raman signals generated in the hollow core of the HC-PCF were guided to the collection optics and were analyzed by a Raman spectrometer for molecular identification.

      Results
      Raman spectra have been obtained successfully from air, reference gases (hydrogen gas, oxygen gas, carbon dioxide gas), and human breath. The limit of detection of the system was found to be approximately 15 parts per million by CO~2~ concentration in the ambient air, characterized by the Raman peaks at 1286 cm[-1] and 1388 cm[-1]. This is a more than 100-fold improvement over the recently reported detection limit with a reflective capillary fibre-based Raman cell. The detection limit can be further improved by changes to the optical configurations, optimizing the interaction length of the HC-PCF and the use of sample pre-concentration method to enhance signal-to-noise ratio.

      Conclusion
      This work demonstrated a working prototype of a simple, compact, and cost-effective breath analyzer based on hollow core photonic crystal fibre and Raman spectroscopy. With further improvement in the detection sensitivity, this method can potentially be used for lung cancer screening.