Cost-effectiveness analysis of positron-emission tomography-computed tomography in preoperative staging for nonsmall-cell lung cancer with resected monometastatic disease

对切除单转移性非小细胞肺癌患者进行术前分期时,正电子发射断层扫描-计算机断层扫描的成本效益分析

阅读:1

Abstract

BACKGROUND: The aim of this study was, from the Chinese healthcare perspective, to assess the cost-effectiveness of positron-emission tomography-computed tomography (PET-CT) with F-fluorodeoxyglucose (F-FDG) in preoperation staging for nonsmall-cell lung cancer (NSCLC) with resected monometastatic disease based on a retrospective study. This study was conducted from January 2017 to February 2019 at an academic hospital. METHODS: A Markov model and 3 decision-tree models were designed to calculate the long-term medical costs, outcomes, and incremental cost-effectiveness ratios (ICERs) of the 2 diagnostic strategies (PET-CT and conventional CT). Model robustness was assessed in sensitivity analyses. RESULTS: For the base-case analysis, preoperative PET-CT evaluation for NSCLC with resected monometastatic disease provided an additional 1.475, 2.129, and 2.412 life-years (LYs), in the time horizon of 10-, 20-, and 30-year, respectively, and the ICERs for the PET-CT group compared with the conventional CT group were $1153, $1393, and $1430 per LY, separately. The acceptability curves demonstrated that when the willingness-to-pay (WTP) thresholds ranged from $500 to $3000/LY, the probability of cost-effectiveness changed varied dramatically, and at WTP > $3000, the probability that the PET-CT group achieved cost-effectiveness was 100%. Sensitivity analyses suggested that the models we designed were robust. CONCLUSION: Compared with conventional CT scan, preoperative F-FDG PET-CT evaluation for patients with resected monometastatic NSCLC is cost-effective from the Chinese healthcare perspective. Preoperative F-FDG PET-CT evaluation should be popularized for patients with resected monometastatic NSCLC.

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。