诊断转移性非小细胞肺癌的快速室内下一代测序:医院预算影响分析》。

IF 2.3 Q2 ECONOMICS
Journal of Health Economics and Outcomes Research Pub Date : 2023-06-26 eCollection Date: 2023-01-01 DOI:10.36469/001c.77686
Ubong Silas, Maximilian Blüher, Antonia Bosworth Smith, Rhodri Saunders
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引用次数: 0

摘要

背景:随着对分子发病机理认识的加深,癌症的靶向治疗越来越常见。使用靶向治疗必须进行分子检测。遗憾的是,检测周转时间可能会延误靶向治疗的启动。研究目的调查在美国医院使用新一代测序 (NGS) 仪器对转移性非小细胞肺癌 (mNSCLC) 进行内部 NGS 检测的影响。方法:采用队列级决策树建立马尔可夫模型,以确定两家医院路径之间的差异。将使用内部 NGS(75%)和使用外部实验室(所谓的送出 NGS)(25%)的路径与完全送出 NGS 的标准进行了比较。该模型从一家美国医院的角度出发,时间跨度为 5 年。所有成本输入数据均为 2021 年美元或膨胀至 2021 年美元。对关键变量进行了情景分析。结果:在一家有 500 名 mNSCLC 患者的医院,估计实施内部 NGS 会增加医院的检测成本和收入。根据模型预测,5 年内检测成本将增加 710 060 美元,收入将增加 1732 506 美元,投资回报为 1022 446 美元。内部 NGS 的投资回收期为 15 个月。使用内部 NGS 时,接受靶向治疗的患者人数增加了 3.38%,平均周转时间缩短了 10 天。讨论:缩短检测周转时间是内部 NGS 的一个优点。这有助于减少因第二意见而流失的 mNSCLC 患者,并增加接受靶向治疗的患者人数。根据模型结果预测,一家美国医院将在 5 年内获得积极的投资回报。该模型反映的是一种建议方案。医院投入的异质性和送出 NGS 的成本意味着需要针对具体情况的投入。结论:使用内部 NGS 检测可缩短检测周转时间,增加接受靶向治疗的患者人数。对医院来说,其他好处还包括:减少了因第二意见而流失的病人,而且内部 NGS 还能带来额外收入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Fast In-House Next-Generation Sequencing in the Diagnosis of Metastatic Non-small Cell Lung Cancer: A Hospital Budget Impact Analysis.

Fast In-House Next-Generation Sequencing in the Diagnosis of Metastatic Non-small Cell Lung Cancer: A Hospital Budget Impact Analysis.

Fast In-House Next-Generation Sequencing in the Diagnosis of Metastatic Non-small Cell Lung Cancer: A Hospital Budget Impact Analysis.

Fast In-House Next-Generation Sequencing in the Diagnosis of Metastatic Non-small Cell Lung Cancer: A Hospital Budget Impact Analysis.

Background: Targeted therapy for cancer is becoming more frequent as the understanding of the molecular pathogenesis increases. Molecular testing must be done to use targeted therapy. Unfortunately, the testing turnaround time can delay the initiation of targeted therapy. Objective: To investigate the impact of a next-generation sequencing (NGS) machine in the hospital that would allow for in-house NGS testing of metastatic non-small cell lung cancer (mNSCLC) in a US setting. Methods: The differences between 2 hospital pathways were established with a cohort-level decision tree that feeds into a Markov model. A pathway that used in-house NGS (75%) and the use of external laboratories (so-called send-out NGS) (25%), was compared with the standard of exclusively send-out NGS. The model was from the perspective of a US hospital over a 5-year time horizon. All cost input data were in or inflated to 2021 USD. Scenario analysis was done on key variables. Results: In a hospital with 500 mNSCLC patients, the implementation of in-house NGS was estimated to increase the testing costs and the revenue of the hospital. The model predicted a $710 060 increase in testing costs, a $1 732 506 increase in revenue, and a $1 022 446 return on investment over 5 years. The payback period was 15 months with in-house NGS. The number of patients on targeted therapy increased by 3.38%, and the average turnaround time decreased by 10 days when in-house NGS was used. Discussion: Reducing testing turnaround time is a benefit of in-house NGS. It could contribute to fewer mNSCLC patients lost to second opinion and an increased number of patients on targeted therapy. The model outcomes predicted that, over a 5-year period, there would be a positive return on investment for a US hospital. The model reflects a proposed scenario. The heterogeneity of hospital inputs and the cost of send-out NGS means context-specific inputs are needed. Conclusion: Using in-house NGS testing could reduce the testing turnaround time and increase the number of patients on targeted therapy. Additional benefits for the hospital are that fewer patients will be lost to second opinion and that in-house NGS could generate additional revenue.

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