A bronchial-airway gene-expression classifier to improve the diagnosis of lung cancer: Clinical outcomes and cost-effectiveness analysis

Bronchoscopy is the safest procedure for lung cancer diagnosis when an invasive evaluation is required after imaging procedures. However, its sensitivity is relatively low, especially for small and peripheral lesions. We assessed benefits and costs of introducing a bronchial gene-expression classifier (BGC) to improve the performance of bronchoscopy and the overall diagnostic process for early detection of lung cancer. We used discrete-event simulation to compare clinical and economic outcomes of two different strategies with the standard practice in former and current smokers with indeterminate nodules: (i) location-based strategy—integrated the BGC to the bronchoscopy indication; (ii) simplified strategy—extended use of bronchoscopy plus BGC also on small and peripheral lesions. Outcomes modeled were rate of invasive procedures, quality-adjusted-life-years (QALYs), costs and incremental cost-effectiveness ratios. Compared to the standard practice, the location-based strategy (i) reduced absolute rate of invasive procedures by 3.3% without increasing costs at the current BGC market price. It resulted in savings when the BGC price was less than $3,000. The simplified strategy (ii) reduced absolute rate of invasive procedures by 10% and improved quality-adjusted life expectancy, producing an incremental cost-effectiveness ratio of $10,109 per QALY. In patients with indeterminate nodules, both BGC strategies reduced unnecessary invasive procedures at high risk of adverse events. Moreover, compared to the standard practice, the simplified use of BGC for central and peripheral lesions resulted in larger QALYs gains at acceptable cost. The location-based is cost-saving if the price of classifier declines.