快速内部新一代测序诊断转移性非小细胞肺癌:医院预算影响分析

IF 2.3 Q2 ECONOMICS
Ubong Silas, Maximilian Blüher, Antonia Bosworth Smith, Rhodri Saunders
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引用次数: 0

摘要

背景:随着对肿瘤分子发病机制了解的增加,靶向治疗越来越频繁。使用靶向治疗必须进行分子检测。不幸的是,测试的周转时间会延迟靶向治疗的开始。目的:研究下一代测序(NGS)设备在医院的影响,该设备将允许在美国进行转移性非小细胞肺癌(mNSCLC)的内部NGS检测。方法:采用队列水平决策树建立两种医院路径之间的差异,并将其输入马尔可夫模型。将使用内部NGS(75%)和使用外部实验室(所谓的发送NGS)(25%)的途径与仅发送NGS的标准进行比较。该模型是从一家美国医院的5年时间范围的角度出发的。所有成本输入数据均为2021美元。对关键变量进行了情景分析。结果:在一家拥有500名小细胞肺癌患者的医院中,估计实施内部NGS会增加医院的检测成本和收入。该模型预测,在5年内,测试成本将增加710 060美元,收入将增加1 732 506美元,投资回报率将达到1 022 446美元。使用内部NGS,投资回收期为15个月。使用内部NGS时,接受靶向治疗的患者数量增加了3.38%,平均周转时间减少了10天。讨论:减少测试周转时间是内部NGS的好处。这可能有助于减少小细胞肺癌患者失去第二意见和增加患者数量的靶向治疗。模型结果预测,在5年的时间里,一家美国医院的投资将获得正回报。该模型反映了一个提议的情景。医院投入的异质性和送出的NGS成本意味着需要针对具体情况的投入。结论:采用内部NGS检测可缩短检测周期,增加接受靶向治疗的患者数量。对医院来说,额外的好处是更少的病人会失去第二意见,而且内部的NGS可以产生额外的收入。
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
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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CiteScore
3.00
自引率
0.00%
发文量
55
审稿时长
10 weeks
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