Economic impact of using risk models for eligibility selection to the International lung screening Trial.

OBJECTIVES: Using risk models as eligibility criteria for lung screening can reduce race and sex-based disparities. We used data from the International Lung Screening Trial(ILST; NCT02871856) to compare the economic impact of using the PLCOm2012 risk model or the US Preventative Services' categorical age-smoking history-based criteria (USPSTF-2013). MATERIALS AND METHODS: The cost-effectiveness of using PLCOm2012 versus USPSTF-2013 was evaluated with a decision analytic model based on the ILST and other screening trials. The primary outcomes were costs in 2020 International Dollars ($), quality-adjusted life-years (QALY) and incremental net benefit (INB, in $ per QALY). Secondary outcomes were selection characteristics and cancer detection rates (CDR). RESULTS: Compared with the USPSTF-2013 criteria, the PLCOm2012 risk model resulted in $355 of cost savings per 0.2 QALYs gained (INB=$4294 at a willingness-to-pay threshold of $20 000/QALY (95 %CI: $4205-$4383). Using the risk model was more cost-effective in females at both a 1.5 % and 1.7 % 6-year risk threshold (INB=$6616 and $6112, respectively), compared with males ($5221 and $695). The PLCOm2012 model selected more females, more individuals with fewer years of formal education, and more people with other respiratory illnesses in the ILST. The CDR with the risk model was higher in females compared with the USPSTF-2013 criteria (Risk Ratio = 7.67, 95 % CI: 1.87-31.38). CONCLUSION: The PLCOm2012 model saved costs, increased QALYs and mitigated socioeconomic and sex-based disparities in access to screening.

Updated cost-effectiveness analysis of lung cancer screening for Australia, capturing differences in the health economic impact of NELSON and NLST outcomes.

BACKGROUND: A national, lung cancer screening programme is under consideration in Australia, and we assessed cost-effectiveness using updated data and assumptions. METHODS: We estimated the cost-effectiveness of lung screening by applying screening parameters and outcomes from either the National Lung Screening Trial (NLST) or the NEderlands-Leuvens Longkanker Screenings ONderzoek (NELSON) to Australian data on lung cancer risk, mortality, health-system costs, and smoking trends using a deterministic, multi-cohort model. Incremental cost-effectiveness ratios (ICERs) were calculated for a lifetime horizon. RESULTS: The ICER for lung screening compared to usual care in the NELSON-based scenario was AU$39,250 (95% CI $18,150-108,300) per quality-adjusted life year (QALY); lower than the NLST-based estimate (ICER = $76,300, 95% CI $41,750-236,500). In probabilistic sensitivity analyses, lung screening was cost-effective in 15%/60% of NELSON-like simulations, assuming a willingness-to-pay threshold of $30,000/$50,000 per QALY, respectively, compared to 0.5%/6.7% for the NLST. ICERs were most sensitive to assumptions regarding the screening-related lung cancer mortality benefit and duration of benefit over time. The cost of screening had a larger impact on ICERs than the cost of treatment, even after quadrupling the 2006-2016 healthcare costs of stage IV lung cancer. DISCUSSION: Lung screening could be cost-effective in Australia, contingent on translating trial-like lung cancer mortality benefits to the clinic.

Applying utility values in cost-effectiveness analyses of lung cancer screening: A review of methods.

Lung cancer screening with low-dose computed tomography (LDCT) in high-risk populations has been shown in randomised controlled trials to lead to early diagnosis and reduced lung cancer mortality. However, investment into screening will largely depend on the outcomes of cost-effectiveness analyses that demonstrate acceptable costs for every quality-adjusted life year (QALY) gained. The methods used to apply utility values to measure QALYs can significantly impact the outcomes of cost-effectiveness analyses and if applied inaccurately can lead to unreliable estimates. We reviewed the use of utility values in 26 cost-effectiveness analyses of lung screening with LDCT conducted between 2005 and 2021, and found considerable variation in methods. Specifically, authors made different assumptions made relating to (i) baseline quality-of-life among screening participants, (ii) potential harms from screening, (iii) utilities and disutilities applied to lung cancer health states, and (iv) quality-of-life for lung cancer survivors. We discuss how each of these assumptions can influence incremental cost-effectiveness ratios. Key recommendations for future evaluations are (i) that modelling studies should justify the choice of baseline utilities, especially if patients are assumed to recover fully after curative treatment; (ii) the impact of false positive scans on quality-of-life should be modelled, at least in sensitivity analyses; (iii) modellers should justify assumptions relating to post-operative recovery, preferably based on knowledge of local practices; (iv) utilities applied to a lung cancer diagnosis should be appropriately sourced and calculated; and (v) adjustment for age-related declines in quality-of-life should be considered, especially for models that examine lifetime horizons.