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Comparative Study
. 2013 Jan 29:13:39.
doi: 10.1186/1471-2407-13-39.

Gene-guided gefitinib switch maintenance therapy for patients with advanced EGFR mutation-positive non-small cell lung cancer: an economic analysis

Affiliations
Comparative Study

Gene-guided gefitinib switch maintenance therapy for patients with advanced EGFR mutation-positive non-small cell lung cancer: an economic analysis

Jun Zhu et al. BMC Cancer. .

Abstract

Background: Maintenance therapy with gefitinib notably improves survival in patients with advanced non-small cell lung cancer (NSCLC) and EGFR mutation-positive tumors, but the economic impact of this practice is unclear.

Methods: A decision-analytic model was developed to simulate 21-day patient transitions in a 10-year time horizon. The clinical data were primarily obtained from the results of a pivotal phase III trial that assessed gefitinib maintenance treatment in patients with advanced NSCLC. The cost data were derived from the perspective of the Chinese health care system. The primary outcome was the incremental cost-effectiveness ratio (ICER) at a willingness-to-pay (WTP) threshold of 3 times the per capita GDP of China. Sensitivity analyses were used to explore the impact of uncertainty regarding the results. The impact of the gefitinib patient assistance program (GPAP) was evaluated.

Results: After EGFR genotyping, gefitinib maintenance treatment for advanced NSCLC with EGFR mutations increased the life expectancy by 0.74 years and 0.46 QALYs compared with routine follow-up at an additional cost of $26,149.90 USD ($7,178.20 with the GPAP). The ICER for gefitinib maintenance was $57,066.40 and $15,664.80 per QALY gained (at a 3% discount rate) without and with the GPAP, respectively. The utility of progression free survival, the hazard ratio of progression-free survival for gefitinib treatment and the cost of gefitinib per dose were the three factors that had the greatest influence on the results.

Conclusions: These results indicate that gene-guided maintenance therapy with gefitinib with the GPAP might be a cost-effective treatment option.

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Figures

Figure 1
Figure 1
The schematics of the decision tree (A) and the Markov state transition model (B).
Figure 2
Figure 2
One-way sensitivity analyses show the lower and upper values for the cost-effectiveness ratio of the Gefitinib strategy to the Control strategy for each parameter.
Figure 3
Figure 3
Two-way sensitivity analysis of the effects of the frequency of EGFR mutations and the cost of EGFR genotyping.
Figure 4
Figure 4
A probabilistic scatter plot of the incremental cost-effectiveness ratio (ICER) between the Control and Gefitinib strategies for a cohort of 1,000 patients. Each dot represents the ICER for 1 simulation. An ellipse surrounds 95% of the estimates. Dots that are located below the ICER threshold represent cost-effective simulations for the active strategy compared with the Control strategy.
Figure 5
Figure 5
The cost-effectiveness acceptability curves showing the probabilities of net benefits achieved by the Gefitinib strategy compared to the Control strategy at different WTP thresholds in advanced NSCLC patients.

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