Abstract
Background
Hungary has the highest incidence of lung cancer in the world (GLOBOCAN, 2018). Since lung cancer is rarely treatable in its advanced stage, one possible way to reduce mortality is early diagnosis and subsequent treatment. The possibility and necessity of introducing low-dose computed tomography (LDCT) lung cancer screening as a public health programme is a current and relevant health policy issue.
Methods
A Markov cohort model was built to assess the cost-effectiveness of such a risk group screening programme in Hungary. The model was populated with transition probabilities and resource utilization data derived from the HUNCHEST Hungarian lung cancer screening trial. The model results are presented in incremental cost-effectiveness ratio.
Results
A closed cohort of 10,000 smokers with the average starting age of 59 years was followed over life-time horizon and screened for lung cancer annually until the age of 74. Compared to the current scenario of no organized lung cancer screening in Hungary, the model resulted in an additional 0.1614 life-year gained per individual and an additional 0.2924 disease-free life-year gained per individual with annual screening frequency. The incremental cost-effectiveness ratio was EUR 608 indicating that assessed intervention is cost-effective in the analyzed setting. Sensitivity analyses confirmed the robustness of the model results.
Conclusions
Results suggest that introducing low-dose computed tomography screening for lung cancer is a cost-effective intervention in Hungary. Considering the exceptionally high incidence and mortality of lung cancer in Hungary, the population could benefit from such a risk group screening programme.
Key messages
Low-dose computed tomography screening for lung cancer is cost-effectiveness in the Hungarian setting. Policy makers are encouraged to consider the introduction of a risk group screening programme.
Cost-effectiveness analyses of Lung Cancer screening strategies using low dose computed tomography – a systematic review