An Application of Iterative Health Economic Evaluation: An Update on the Early Cost Effectiveness of Whole-Genome Sequencing in Advanced Non-small-Cell Lung Cancer.

Abstract

OBJECTIVE: Whole genome sequencing (WGS) can identify more druggable targets than the standard of care (SoC) panels, however, its health effects and costs are highly uncertain. Given the rapidly evolving treatment landscape and pricing, an iterative approach is crucial to continuously reassess evidence and adapt economic models. Our objective was to update a previously developed economic model for WGS. METHODS: We used a structured approach to identify and report model elements requiring updates, based on established tools and methodological guidance, and applied it to the probabilistic decision model by Simons et al.(2021), which compared SoC, WGS, and SoC followed by WGS in patients with inoperable stage IIIB, C/IV NSCLC in the Dutch setting. RESULTS: Updates included a new treatment (sotorasib), revised drug and diagnostic costs, and adherence to the latest guidelines. Drug and WGS diagnostics costs fell by 8% and 26%, respectively. SoC diagnostic prices increased by 17%. We explored the impact of the prevalence of druggable targets, effectiveness of off-label treatments, (academic-specific) diagnostic costs, and price negotiations. The ICER of WGS versus SoC decreased from €737,197 to €419,053/QALY. WGS would become cost-effective if diagnostic costs descended from €2,180 to €1,246 or if additional druggable targets were identified in ≥3.3% of patients. CONCLUSION: Our structured approach effectively identified items in the original analysis requiring updates and provides a foundation for further developing a checklist to guide iterative HTA. Continued monitoring and assessment of new treatment options, the dynamic diagnostics and costs throughout the life-cycle remain necessary to determine when WGS can be considered cost-effective.