Cost-Effectiveness Analysis of Gefitinib Plus Chemotherapy versus Gefitinib Alone for Advanced Non-Small-Cell Lung Cancer with EGFR Mutations in China

在中国,吉非替尼联合化疗与吉非替尼单药治疗EGFR突变晚期非小细胞肺癌的成本效益分析

阅读:1

Abstract

OBJECTIVE: The aim of this study was to evaluate the cost-effectiveness of gefitinib plus chemotherapy (GCP) versus gefitinib alone for advanced non-small-cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutations in China. METHODS: A decision-analytic Markov model was conducted to simulate the disease process of advanced NSCLC patients with EGFR mutations. Three distinct health states: progression-free survival (PFS), progressive disease (PD) and death were included. Clinical data were derived from the NEJ009 study. The cost was evaluated from the perspective of the Chinese society. Quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICER) were calculated over a 10-year lifetime horizon. One-way sensitivity analysis and probabilistic sensitivity analysis were also performed to explore the uncertainty of parameters in the study. RESULTS: The base case analysis demonstrated that gefitinib plus chemotherapy gained 2.44 QALYs at an average cost of $59,571.34, while the effectiveness and cost of gefitinib group were 1.82 QALYs and $52,492.75, respectively. The ICER for gefitinib plus chemotherapy was $11,499.98 per QALY gained. The ICER was lower than the accepted willingness-to-pay (WTP) threshold, which was three times gross domestic product (GDP) per capita of China ($31,498.70 per QALY). Variation of parameters did not reverse the cost-effectiveness of gefitinib plus chemotherapy through univariable and probabilistic sensitivity analyses. CONCLUSION: Our results showed that gefitinib plus chemotherapy is a cost-effective treatment option compared with gefitinib for advanced NSCLC patients with EGFR mutations in China.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。