National recommendations for lung cancer screening for former and current smokers aged 55-80 years with a 30-pack-year smoking history create demand to implement efficient and effective systems to offer smoking cessation on a large scale. These older, high-risk smokers differ from participants in past clinical trials of behavioral and pharmacologic interventions for tobacco dependence. There is a gap in knowledge about how best to design systems to extend reach and treatments to maximize smoking cessation in the context of lung cancer screening. Eight clinical trials, seven funded by the National Cancer Institute and one by the Veterans Health Administration, address this gap and form the SCALE (Smoking Cessation within the Context of Lung Cancer Screening) collaboration. This paper describes methodological issues related to the design of these clinical trials: clinical workflow, participant eligibility criteria, screening indication (baseline or annual repeat screen), assessment content, interest in stopping smoking, and treatment delivery method and dose, all of which will affect tobacco treatment outcomes. Tobacco interventions consider the "teachable moment" offered by lung cancer screening, how to incorporate positive and negative screening results, and coordination of smoking cessation treatment with clinical events associated with lung cancer screening. Unique data elements, such as perceived risk of lung cancer and costs of tobacco treatment, are of interest. Lung cancer screening presents a new and promising opportunity to reduce morbidity and mortality resulting from lung cancer that can be amplified by effective smoking cessation treatment. SCALE teamwork and collaboration promise to maximize knowledge gained from the clinical trials.
Scientific Knowledge on the Subject: COPD progresses over decades so little is known about longitudinal changes in individual patients, and whether there are different patterns of disease progression in different patient subgroups.What this Study Adds to the Field: Computational modelling of CT biomarkers suggests there are two patterns of disease progression in COPD. These disease progression patterns or 'subtypes' can be used to stratify individuals into two groups with distinct clinical characteristics, and to stage individuals along their disease time-course. Early stages of both subtypes are identifiable in a proportion of 'healthy smokers' providing a biomarker of early COPD.
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