Incorporating High-Risk Individuals Beyond Smoking History Into Lung Cancer Screening in Hong Kong: A Cost-Effectiveness Study

Abstract

Introduction: Lung cancer (LC) accounts for 26.4% of all cancer deaths in Hong Kong (HK). Lung cancer screening (LCS) with low-dose computed tomography (LDCT) can reduce LC mortality. The cost-effectiveness of LDCT screening in high-risk individuals on the basis of smoking history has previously been investigated. However, nearly half of patients with LC in HK never smoke, indicating a different LC epidemiology compared with Western countries, where most LC cases are associated with smoking. We conducted a cost-effectiveness analysis for LCS, utilizing local data and expanding the target population to include we not only high-risk individuals identified on the basis of smoking history but also those identified through other risk factors.

Methods: A decision tree combined with a state-transition Markov model was developed to simulate identification, diagnosis, and treatments for high-risk individuals, from a health care provider perspective. The selection criteria and screening effectiveness for high-risk individuals on the basis of smoking history were obtained from the Dutch-Belgian Lung Cancer Screening Study, targeting heavy smokers aged 50 to 74 years; whereas the Taiwan Lung Cancer Screening in Never-Smoker Trial was used to model high-risk individuals on the basis of factors other than smoking history. Local LC survival and cost data were used to populate the model. The willingness-to-pay threshold used in the study was US$24,302 to US$40,202 per quality-adjusted life-year (QALY).

Results: Screening led to additional early LC detected, and LC mortality reduction, compared with no screening. Over a lifetime horizon, the incremental cost-effectiveness ratio for high-risk individuals on the basis of smoking history was US$14,122 per QALY. The incremental cost-effectiveness ratio for high-risk individuals on the basis of factors other than smoking history was lower at US$9610 per QALY.

Conclusion: LCS with LDCT can be considered cost-effective in HK for high-risk individuals on the basis of smoking history and factors other than smoking history, contributing to the health benefits of the population. Our findings support a population-based LCS for all high-risk individuals identified through criteria beyond smoking history.

Keywords: High-risk individuals; LDCT; Lung cancer; Lung cancer screening; Smoking history.

Figure 1

Tornado diagrams from the one-way sensitivity analysis. The diagrams illustrate the impact of varying key input parameters on the ICER of lung cancer screening compared with no screening. Parameters are ranked by the magnitude of their influence on the ICER, with the most influential at the top. Bars extending to the left or right indicate the direction and extent of change in the ICER when the parameter is varied across its plausible range. Smoking cohort refers to high-risk individuals on the basis of smoking history. Non smoker cohort refers to high-risk individuals on the basis of factors other than smoking history. ICER, incremental cost-effectiveness ratio; LC, lung cancer; CT, computed tomography.

Figure 2

The incremental cost-effectiveness scatterplot for high-risk individuals on the basis of smoking history. Each point represents a simulation from the probabilistic sensitivity analysis, illustrating the difference in costs and QALYs between the screened and nonscreened groups. The scatterplot illustrates the uncertainty around the estimated incremental cost-effectiveness ratio for the screening strategy. QALY, quality-adjusted life years.

Figure 3

The incremental cost-effectiveness scatterplot for high-risk individuals on the basis of factors other than smoking history. Each point represents a simulation from the probabilistic sensitivity analysis, showing the difference in costs and QALYs between the screened and nonscreened groups. The scatterplot illustrates the uncertainty around the estimated incremental cost-effectiveness ratio for the screening strategy.