RESUMEN
This study assessed the cost-effectiveness of a lung cancer screening (LCS) program using low-dose computed tomography (LDCT) in Austria. An existing decision tree with an integrated Markov model was used to analyze the cost-effectiveness of LCS versus no screening from a healthcare payer perspective over a lifetime horizon. A simulation was conducted to model annual LCS for an asymptomatic high-risk population cohort aged 50-74 with a smoking history using the Dutch-Belgian Lung Cancer Screening Study (NEderlands-Leuvens Longkanker ScreeningsONderzoek, NELSON) screening outcomes. The principal measure utilized to assess cost-effectiveness was the incremental cost-effectiveness ratio (ICER). Sensitivity and scenario analyses were employed to determine uncertainties surrounding the key model inputs. At an uptake rate of 50%, 300,277 eligible individuals would participate in the LCS program, yielding 56,122 incremental quality-adjusted life years (QALYs) and 84,049 life years gained compared to no screening, with an ICER of EUR 24,627 per QALY gained or EUR 16,444 per life-year saved. Additionally, LCS led to the detection of 25,893 additional early-stage lung cancers and averted 11,906 premature lung cancer deaths. It was estimated that LCS would incur EUR 945 million additional screening costs and EUR 386 million additional treatment costs. These estimates were robust in sensitivity analyses. Implementation of annual LCS with LDCT for a high-risk population, using the NELSON screening outcomes, is cost-effective in Austria, at a threshold of EUR 50,000 per QALY.
RESUMEN
OBJECTIVES: This study aimed to evaluate the cost-effectiveness of lung cancer screening (LCS) with volume-based low-dose computed tomography (CT) versus no screening for an asymptomatic high-risk population in the United Kingdom (UK), utilising the long-term insights provided by the NELSON study, the largest European randomized control trial investigating LCS. METHODS: A cost-effectiveness analysis was conducted using a decision tree and a state-transition Markov model to simulate the identification, diagnosis, and treatments for a lung cancer high-risk population, from a UK National Health Service (NHS) perspective. Eligible participants underwent annual volume CT screening and were compared to a cohort without the option of screening. Screen-detected lung cancers, costs, quality-adjusted life years (QALYs), and the incremental cost-effectiveness ratio (ICER) were predicted. RESULTS: Annual volume CT screening of 1.3 million eligible participants resulted in 96,474 more lung cancer cases detected in early stage, and 73,825 fewer cases in late stage, leading to 53,732 premature lung cancer deaths averted and 421,647 QALYs gained, compared to no screening. The ICER was £5,455 per QALY. These estimates were robust in sensitivity analyses. LIMITATIONS: Lack of long-term survival data for lung cancer patients; deficiency in rigorous micro-costing studies to establish detailed treatment costs inputs for lung cancer patients. CONCLUSIONS: Annual LCS with volume-based low-dose CT for a high-risk asymptomatic population is cost-effective in the UK, at a threshold of £20,000 per QALY, representing an efficient use of NHS resources with substantially improved outcomes for lung cancer patients, as well as additional societal and economic benefits for society as a whole. These findings advocate evidence-based decisions for the potential implementation of a nationwide LCS in the UK.