Abstract
BACKGROUND: The cost-effectiveness of sotorasib and its reasonable price in the United States (US) and China remain unknown. Our objective was to estimate the price at which sotorasib could be economical as second-line treatment for advanced non-small-cell lung cancer patients with Kirsten rat sarcoma viral oncogene homolog p.G12C-mutation in 2 countries. METHODS: We conducted an economic evaluation from the perspective of US and Chinese payers. To analyze US patients, we built a partitioned survival model. However, since we lacked Asian-specific overall survival data, we created a state transition model for the Chinese patients. We obtained patients' baseline characteristics and clinical data from CodeBreaK200, while utilities and costs were gathered from public databases and published literature. We calculated costs (US dollar), life years, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios. We conducted price simulation to guide pricing strategies. Additionally, we assessed the reliability of our results through sensitivity analyses, scenario analyses, and subgroup analyses. RESULTS: The incremental cost-effectiveness ratios of sotorasib compared to docetaxel were $1501,852 per quality-adjusted life-years (QALY) in the US and $469,106/QALY in China, respectively, which meant sotorasib was unlikely to be economical at the currently available price of $20,878 (240 × 120 mg) in both countries. Price simulation results revealed that sotorasib would be preferred at a price lower than $1400 at the willingness-to-pay threshold of $37,376 in China and a price lower than $2220 at the willingness-to-pay threshold of $150,000 in the US. Sensitivity, scenario, and subgroup analyses showed that these conclusions were generally robust, the model was most sensitive to the utilities of progression-free survival and post-progression survival. CONCLUSIONS: Sotorasib could potentially be a cost-effective therapy in the US and China following price reductions. Our evidence-based pricing strategy can assist decision-makers and clinicians in making optimal decisions. However, further analysis of budget impact and affordability is needed.