Systematic review of the cost-effectiveness of screening for lung cancer with low dose computed tomography

Abstract

ObjectivesLung cancer (LC) remains a burden for patients and healthcare systems, with most cases only diagnosed once disease is late stage. Screening for LC with low-dose computed tomography (LDCT) has shown a stage shift and led to a lung cancer-specific mortality reduction. Economic evaluations have been conducted which explore the benefits and costs of screening, however, previous systematic reviews concluded results were heterogeneous. LC screening has evolved and there have been further cost-effectiveness analyses conducted.The aim of this study was to provide an up-to-date systematic review of the cost-effectiveness of LC screening with LDCT. Methods and MaterialsDatabases were searched for full papers published in English 01/1994–02/2022. Inclusion criteria was full economic evaluation of LC screening using LDCT compared to either no screening or chest X-ray. ResultsForty-five evaluations were identified, three conducted alongside trials and 42 modelling studies. Thirty-nine evaluations (86.7%) found LC screening with LDCT to be cost-effective. Several findings were broadly consistent across studies: cost-effectiveness was optimal in those age 55–75 years and smoking history of at least 20 pack-years. Biennial screening was often more cost-effective than annual screening and would likely result in less additional findings and radiation exposure. A smoking cessation intervention alongside screening improved cost-effectiveness, but which intervention was optimal was unclear. Risk predictions models using more parameters to target participants for screening did not have more benefits than those using age and smoking alone, and cost-effectiveness was equivalent. Cost-effectiveness was sensitive to cost and specificity of LDCT, and disutility associated with screening. ConclusionOverall, LC screening with LDCT is cost-effective in a high-risk population. Questions remain regarding risk prediction models, smoking cessation interventions and appropriateness of utility values in the screened population. Once these uncertainties are addressed, further economic evaluation may be required to inform policymakers prior to implementation.