The evaluation of cancer control interventions in lung cancer using the Canadian Cancer Risk Management Model

Clinical impact and cost-effectiveness of integrating smoking cessation into lung cancer screening: a microsimulation model

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.

Biennial lung cancer screening in Canada with smoking cessation-outcomes and cost-effectiveness

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.

The Population Health Model (POHEM): an overview of rationale, methods and applications

The POpulation HEalth Model (POHEM) is a health microsimulation model that was developed at Statistics Canada in the early 1990s. POHEM draws together rich multivariate data from a wide range of sources to simulate the lifecycle of the Canadian population, specifically focusing on aspects of health. The model dynamically simulates individuals’ disease states, risk factors, and health determinants, in order to describe and project health outcomes, including disease incidence, prevalence, life expectancy, health-adjusted life expectancy, quality of life, and healthcare costs. Additionally, POHEM was conceptualized and built with the ability to assess the impact of policy and program interventions, not limited to those taking place in the healthcare system, on the health status of Canadians. Internationally, POHEM and other microsimulation models have been used to inform clinical guidelines and health policies in relation to complex health and health system problems. This paper provides a high-level overview of the rationale, methodology, and applications of POHEM. Applications of POHEM to cardiovascular disease, physical activity, cancer, osteoarthritis, and neurological diseases are highlighted.

Measuring the population impact of introducing stereotactic ablative radiotherapy for stage I non-small cell lung cancer in Canada

BACKGROUND

The Cancer Risk Management Model (CRMM) was used to estimate the health and economic impact of introducing stereotactic ablative radiotherapy (SABR) for stage I non-small cell lung cancer (NSCLC) in Canada.

METHODS

The CRMM uses Monte Carlo microsimulation representative of all Canadians. Lung cancer outputs were previously validated internally (Statistics Canada) and externally (Canadian Cancer Registry). We updated costs using the Ontario schedule of fees and benefits or the consumer price index to calculate 2013 Canadian dollars, discounted at a 3% rate. The reference model assumed that for stage I NSCLC, 75% of patients undergo surgery (lobectomy, sublobar resection, or pneumonectomy), 12.5% undergo radiotherapy (RT), and 12.5% undergo best supportive care (BSC). SABR was introduced in 2008 as an alternative to sublobar resection, RT, and BSC at rates reflective of the literature. Incremental cost effectiveness ratios (ICERs) were calculated; a willingness-to-pay threshold of $100,000 (all amounts are in Canadian dollars) per quality-adjusted life-year (QALY) was used from the health care payer perspective.

RESULTS

The total cost for 25,085 new cases of lung cancer in 2013 was calculated to be $608,002,599. Mean upfront costs for the 4,318 stage I cases were $7,646.98 for RT, $8,815.55 for SABR, $12,161.17 for sublobar resection, $16,266.12 for lobectomy, $22,940.59 for pneumonectomy, and $14,582.87 for BSC. SABR dominated (higher QALY, lower cost) RT, sublobar resection, and BSC. RT had lower initial costs than SABR that were offset by subsequent costs associated with recurrence. Lobectomy was cost effective when compared with SABR, with an ICER of $55,909.06.

CONCLUSION

The use of SABR for NSCLC in Canada is projected to result in significant cost savings and survival gains.