Cost-effectiveness of volume computed tomography in lung cancer screening: a cohort simulation based on Nelson study outcomes

Abstract

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.

Keywords:

• Cost-effectiveness
• lung cancer
• screening
• computed tomography
• NELSON

JEL CLASSIFICATION CODES:

• D61
• D6
• D
• D60

Transparency

Declaration of financial/other interests

X.P., D.R. and H.B. are employed by iDNA. E.D. and M.O have a financial interest in iDNA. J.R. is employed by AstraZeneca and owns shares in the company. D.B. reports lecture fees from MSD, BMS, Roche, and AstraZeneca; he is the advisor to UK National Screening Committee. H.JM.G reports grants from Cancer-id EU funding and Interreg grant outside the submitted work; consulting fees from Eli Lilly and Novartis. M.J.P reports EU grants outside the submitted work; personal fees from Asc Academics; he is the shareholder at Health-Ecore in Zeist (NL) and Pharmacoeconomics Advice in Groningen (NL).

Author contributions

X.P., E.D., D.R., and R.V. designed the model and the computational framework. M.P. verified the analytical method. X.P., D.R., and H.B. performed the modelling. J.R worked out the model technique critique. D.B., H.G., and M.O supported with clinical validation for the model parameters. X.P. took the lead in writing the manuscript. All authors provided critical feedback and helped shape the research, analysis and manuscript.

Acknowledgements

No assistance in the preparation of this article is to be declared.

Reviewer disclosures

Peer reviewers on this manuscript have received an honorarium from JME for their review work but have no other relevant financial relationships to disclose.

Previous presentations

An abstract based on the research was presented as a poster in the conference ISPOR Europe 2022 conference in Vienna.

Additional information

Funding

This work was funded by AstraZeneca PLC.