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Background: Low-dose computed tomography (CT) screening can reduce lung cancer mortality in people at high risk; adding a smoking cessation intervention to screening could further improve screening program outcomes. This study aimed to assess the impact of adding a smoking cessation intervention to lung cancer screening on clinical outcomes, costs and cost-effectiveness., Methods: Using the OncoSim-Lung mathematical microsimulation model, we compared the projected lifetime impact of a smoking cessation intervention (nicotine replacement therapy, varenicline and 12 wk of counselling) in the context of annual low-dose CT screening for lung cancer in people at high risk to lung cancer screening without a cessation intervention in Canada. The simulated population consisted of Canadians born in 1940-1974; lung cancer screening was offered to eligible people in 2020. In the base-case scenario, we assumed that the intervention would be offered to smokers up to 10 times; each intervention would achieve a 2.5% permanent quit rate. Sensitivity analyses varied key model inputs. We calculated incremental cost-effectiveness ratios with a lifetime horizon from the health system's perspective, discounted at 1.5% per year. Costs are in 2019 Canadian dollars., Results: Offering a smoking cessation intervention in the context of lung cancer screening could lead to an additional 13% of smokers quitting smoking. It could potentially prevent 12 more lung cancers and save 200 more life-years for every 1000 smokers screened, at a cost of $22 000 per quality-adjusted life-year (QALY) gained. The results were most sensitive to quit rate. The intervention would cost over $50 000 per QALY gained with a permanent quit rate of less than 1.25% per attempt., Interpretation: Adding a smoking cessation intervention to lung cancer screening is likely cost-effective. To optimize the benefits of lung cancer screening, health care providers should encourage participants who still smoke to quit smoking., Competing Interests: Competing interests: None declared., (Copyright 2020, Joule Inc. or its licensors.)

Background: Guidelines recommend low-dose CT (LDCT) screening to detect lung cancer among eligible at-risk individuals. We used the OncoSim model (formerly Cancer Risk Management Model) to compare outcomes and costs between annual and biennial LDCT screening., Methods: OncoSim incorporates vital statistics, cancer registry data, health survey and utility data, cost, and other data, and simulates individual lives, aggregating outcomes over millions of individuals. Using OncoSim and National Lung Screening Trial eligibility criteria (age 55-74, minimum 30 pack-year smoking history, smoking cessation less than 15 years from time of first screen) and data, we have modeled screening parameters, cancer stage distribution, and mortality shifts for screen diagnosed cancer. Costs (in 2008 Canadian dollars) and quality of life years gained are discounted at 3% annually., Results: Compared with annual LDCT screening, biennial screening used fewer resources, gained fewer life-years (61,000 vs. 77,000), but resulted in very similar quality-adjusted life-years (QALYs) (24,000 vs. 23,000) over 20 years. The incremental cost-effectiveness ratio (ICER) of annual compared with biennial screening was $54,000-$4.8 million/QALY gained. Average incremental CT scan use in biennial screening was 52% of that in annual screening. A smoking cessation intervention decreased the average cost-effectiveness ratio in most scenarios by half., Conclusions: Over 20 years, biennial LDCT screening for lung cancer appears to provide similar benefit in terms of QALYs gained to annual screening and is more cost-effective. Further study of biennial screening should be undertaken in population screening programs. A smoking cessation program should be integrated into either screening strategy., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

Objective: The objective of this study was to find out the level of knowledge the physicians and lay people have pertaining to the effect of cigarettes, why certain physicians smoke and what measures could be applied to reduce the rate of smoking., Methods: A questionnaire was administered to the one hundred physicians who smoke, one hundred non-smoking physicians and one hundred lay people who smoke to determine their attitude towards this addition. Subjects were chosen using convenience sampling. The physicians were picked from six hospitals of Karachi., Results: When the smoking physicians were asked what could motivate them to stop smoking, majority of them said that an occurrence of a smoking related illness would. Majority of the physicians who do not smoke felt that individual will was the greatest force keeping them from smoking. When asked how smoking can be reduced in Pakistan, majority of the physicians, both smoking and non-smoking, favoured mass health education. Lay smokers expressed marked ignorance about deleterious effects of cigarette smoke. Like smoking physicians, majority of them said that occurrence of an illness related to smoking would effectively motivate them to stop smoking., Conclusion: Based on this survey we conclude that mass health education and enforcement of the ban on smoking in public places will effectively reduce the number of smokers. There is a need to educate physicians and the general public about the cardiac and carcinogenic effects of smoking.

Background: Smoking is responsible for nearly 85% of lung cancer cases and 30% of all cancer-related deaths. Canada has set an ambitious target to reduce tobacco use to 5% by 2035 in alignment with a world-wide tobacco endgame initiative. Aim: We project the impact of achieving a national 5% smoking prevalence rate by 2035 on population-level lung cancer outcomes and costs. Methods: OncoSim-Lung (version 2.5), led by the Canadian Partnership Against Cancer with model development by Statistics Canada, is a microsimulation model that incorporates Canadian demographics, risk factors, registry data, resource utilization and other data to project clinical and economic impacts of cancer control measures. Smoking cessation parameters were modified to reduce the current average national smoking prevalence rate of 18% over time to 5% in 2035. Impacts were compared with those in a reference scenario, which maintained the current prevalence rate. Outputs of interest included lung cancer incidence, mortality, treatment costs, and quality-adjusted life-years (QALYs). Costs and QALYs are undiscounted and reported in 2016 CAD. Results: Achieving a 5% smoking rate by 2035 would result in a 2017-2035 cumulative total of 31,000 fewer lung cancer cases, 21,000 fewer lung cancer-related deaths, and 457,000 additional QALYs compared with projections based on a constant smoking prevalence rate of ∼20%. When stratified by sex, there would be 15,600 and 15,700 fewer lung cancer diagnoses and 11,000 and 10,000 fewer lung cancer-related deaths for males and females respectively. Furthermore, treatment-related costs would be reduced by $680 million dollars. On average there would be 4,500 fewer lung cancer cases, 3,500 fewer deaths, and $35 million in cost savings annually. If a 5% smoking rate is sustained until 2050, then there would be a 15% reduction in lung cancer cases and a 13% reduction in deaths from 2017-2050. Conclusion: Reducing Canada's smoking prevalence to 5% by 2035 could result in a significant reduction in lung cancer cases, deaths and treatment costs. Like Canada, other countries with relatively high smoking prevalence could use averted treatment costs to offset costs of aggressive smoking prevention and cessation programs or redirect them to other healthcare services. [ABSTRACT FROM AUTHOR]

Background: Demonstrated lung cancer mortality reductions through low-dose computed tomography (LDCT) has encouraged some jurisdictions to consider implementing organized LDCT screening. A retrospective analysis of former smokers in the National Lung Screening Trial (NLST) suggested that abstention from smoking coupled with low-dose computed tomography (LDCT) screening realized more mortality benefits than abstinence alone or LDCT alone. Aim: We evaluated the potential costs and cost-effectiveness of lung cancer screening with integrated smoking cessation using OncoSim-Lung (version 2.5), a microsimulation model led by the Canadian Partnership Against Cancer, with model development by Statistics Canada. Methods: We compared organized LDCT screening without smoking cessation to various plausible scenarios of screening with cessation. Assumptions included: annual screening of 55-74 year-old individuals with a 30-pack-yr history; a 42% participation rate reached over 10 years; cessation therapy (nicotine replacement therapy + varenicline + 12 weeks' counseling) at a cost of $490; and up to 10 cessation attempts, with a permanent quit rate of 5% per attempt. Cost-effectiveness was estimated with a lifetime horizon, health system perspective and 1.5% discount rate. Costs are in 2016 CAD. Results: OncoSim-Lung projected that LDCT screening integrated with cessation would cost approximately $76 million annually (undiscounted) from 2017 to 2036 in Canada. About 110 fewer lung cancer (LC) cases and 50 fewer LC deaths would occur annually, compared with screening without cessation. Additionally, many other smoking-related deaths would be prevented. Using a lifetime horizon, smoking cessation would cost $14,000/QALYs gained. In one-way sensitivity analysis, with a 72% participation rate there would be 260 fewer deaths, at $24,000/QALY. With a 10% quit rate, cost-effectiveness would improve to $6,000/QALY. A 50% increase in the cost of the cessation intervention would decrease cost-effectiveness to $22,000/QALY. Conclusion: Robust smoking cessation efforts within a LDCT screening program could save lives and be relatively cost-effective. Cancer control planners should consider integrating smoking cessation when implementing a lung cancer screening initiative. [ABSTRACT FROM AUTHOR]

Background: Cancer control interventions exert their effects over multiple decades. To evaluate diverse and competing opportunities to reduce future cancer burden it is desirable to understand long-term effects prior to any new program implementation or significant change. Internationally, modeling is becoming an accepted source of planning information for decision-makers. Aim: We will describe the construction and use of the OncoSim microsimulation model, which was developed to evaluate cancer control strategies in Canada. Methods: OncoSim is a suite of models (cancers of the lung, colorectum, cervix and breast, plus a composite 32-cancer model) used to address key policy questions and support decision-making. It is led by the Canadian Partnership Against Cancer with model development by Statistics Canada. OncoSim incorporates risk factors, cancer natural history, screening, treatment, survival and end-of-life care. Wherever possible it is informed by Canadian data sources. Models are calibrated to reproduce a range of cancer-specific statistics, e.g., current and historical Canadian cancer-specific incidence and mortality, smoking patterns, and results of screening. The site-specific models have undergone further validation by replicating reported short-term effects of cancer prevention and screening interventions. Users may customize interventions through modifying input parameters. Outputs include incidence, mortality, costs, cost-effectiveness, and resource utilization. Users from the public sector have access at no cost to OncoSim and receive extensive support from a multidisciplinary technical team. The model is continually updated to incorporate emerging knowledge. Results: OncoSim has been used to support cancer control decision-making at the national and provincial/territorial levels. Applications include: national guidelines recommendations for colorectal and lung cancer screening; comparison of cytology vs. HPV based cervical cancer screening; and integration of smoking cessation into low-dose CT lung cancer screening. Conclusion: Validated simulation models such as OncoSim can be a versatile and efficient tool for cancer control planners to evaluate and prioritize cancer control strategies. [ABSTRACT FROM AUTHOR]