Economic Evaluation of a Novel Lung Cancer Diagnostic in a Population of Patients with a Positive Low-Dose Computed Tomography Result.

IF 2.3 Q2 ECONOMICS Journal of Health Economics and Outcomes Research Pub Date : 2024-09-17 eCollection Date: 2024-01-01 DOI:10.36469/001c.121512
Michael J Morris, Sheila A Habib, Maggie L Do Valle, John E Schneider
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Abstract

Background: Early detection of lung cancer is crucial for improving patient outcomes. Although advances in diagnostic technologies have significantly enhanced the ability to identify lung cancer in earlier stages, there are still limitations. The alarming rate of false positives has resulted in unnecessary utilization of medical resources and increased risk of adverse events from invasive procedures. Consequently, there is a critical need for advanced diagnostics after an initial low-dose computed tomography (LDCT) scan. Objectives: This study evaluated the potential cost savings for US payers of CyPath® Lung, a novel diagnostic tool utilizing flow cytometry and machine learning for the early detection of lung cancer, in patients with positive LDCT scans with indeterminate pulmonary nodules (IPNs) ranging from 6 to 29 mm. Methods: A cost offset model was developed to evaluate the net expected savings associated with the use of CyPath® Lung relative to the current standard of care for individuals whose IPNs range from 6 to 29 mm. Perspectives from both Medicare and private payers in a US setting are included, with a 1-year time horizon. Cost calculations included procedure expenses, complication costs, and diagnostic assessment costs per patient. Primary outcomes of this analysis include cost savings per cohort and cost savings per patient. Results: Our analysis showed positive cost savings from a private payer's perspective, with expected savings of 895 202 311 p e r c o h o r t a n d 6460 per patient, across all patients. Scenario analysis resulted in cost savings of 890 829 889 p e r c o h o r t , a n d 6429 per patient. Similarly, savings of 378 689 020 p e r c o h o r t o r 2733 per patient were yielded for Medicare payers, across all patients. In addition, scenario analysis accounting for false negative patients from a Medicare payer perspective yielded savings of 376 902 203 p e r c o h o r t a n d 2720 per patient. Discussion: The results suggest substantial cost savings, primarily due to reductions in follow-up diagnostic assessments and procedures, and highlight the importance of accurate diagnostic tools in reducing unnecessary healthcare expenditures. Conclusion: CyPath® Lung utilization yields savings for private and Medicare payers relative to the current standard of care in a US setting for individuals with 6 to 20 mm IPNs.

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低剂量计算机断层扫描阳性患者群体中一种新的肺癌诊断方法的经济评价。
背景:早期发现肺癌对改善患者预后至关重要。尽管诊断技术的进步大大提高了在早期阶段识别肺癌的能力,但仍然存在局限性。假阳性的惊人比率导致了不必要的医疗资源的利用,并增加了侵入性手术不良事件的风险。因此,在初始低剂量计算机断层扫描(LDCT)扫描后,迫切需要高级诊断。目的:本研究评估了CyPath®Lung(一种利用流式细胞术和机器学习进行肺癌早期检测的新型诊断工具)对LDCT扫描呈阳性且肺结节(ipn)范围为6至29 mm的患者的潜在成本节约。方法:开发了一个成本抵消模型,以评估相对于ipn范围为6至29 mm的个体的当前护理标准,使用CyPath®Lung相关的净预期节省。包括美国医疗保险和私人支付者的视角,时间跨度为1年。成本计算包括每位患者的手术费用、并发症费用和诊断评估费用。该分析的主要结果包括每个队列的成本节约和每个患者的成本节约。结果:从私人付款人的角度来看,我们的分析显示了积极的成本节约,预计在所有患者中,每名患者可节省895 202 311英镑,每名患者可节省6460英镑。情景分析结果显示,每名患者可节省890 - 829 - 889美元的费用,每名患者可节省6429美元。同样,在所有患者中,医疗保险支付者每名患者可节省378 689 020美元,而医疗保险支付者每名患者可节省378 689 020美元。此外,从医疗保险支付者的角度考虑假阴性患者的情景分析产生了376 902 203英镑的储蓄,而从医疗保险支付者的角度来看,每名患者的储蓄为376 902 203英镑。讨论:结果表明大量的成本节约,主要是由于减少了后续诊断评估和程序,并强调了准确的诊断工具在减少不必要的医疗保健支出方面的重要性。结论:相对于目前美国6 - 20毫米ipn患者的护理标准,CyPath®肺的使用为私人和医疗保险支付者节省了费用。
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CiteScore
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自引率
0.00%
发文量
55
审稿时长
10 weeks
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