Clinical outcomes and cost-utility analysis of GKRS plus TKIs versus TKIs in patients with EGFR-mutant lung adenocarcinoma and brain metastases: a Markov decision model.

OBJECTIVE

This study focuses on epidermal growth factor receptor-mutated lung adenocarcinoma, known for frequent brain metastasis. It aimed to compare the clinical outcomes and cost-effectiveness of combining Gamma Knife radiosurgery (GKRS) with tyrosine kinase inhibitors (TKIs) (GKRS+TKI group) versus TKIs alone (TKI group) for the treatment of patients with newly diagnosed brain metastasis in this condition.

METHODS

Study characteristics of the two groups were matched using inverse probability of treatment weighting (IPTW). In the incremental cost-utility ratio (ICUR) model, a healthcare provider perspective, a 1-month cycle length, a 5-year time horizon, and a discount rate of 2% per year for both effectiveness and costs were adopted. Probabilistic and one-way sensitivity analyses were also conducted to demonstrate the robustness of the findings. Statistical analysis was performed using IBM SPSS version 23.0, and cost-effectiveness analysis was conducted using TreeAge Pro software.

RESULTS

After applying IPTW, the GKRS+TKI group included 205 patients, and the TKI group consisted of 102 patients, with no statistically significant differences in whole confounders. The GKRS+TKI group demonstrated significantly prolonged median progression-free survival (37.5 months vs 10.6 months, p < 0.001) and median overall survival (55.1 months vs 30.8 months, p < 0.001) compared with the TKI group. The GKRS plus TKI strategy achieved an ICUR of $30,532.25 per quality-adjusted life year relative to the TKIs at the willingness-to-pay threshold of US$33,059 (Taiwan's per capita gross domestic product).

CONCLUSIONS

The use of GKRS plus TKIs not only reduces disease recurrence and improves prognosis but also demonstrates a higher level of cost-effectiveness. These findings offer valuable guidelines for clinicians and inform healthcare authorities in optimizing resource allocation for improved medical care.