Hammer Mark M, Gupta Sumit, Kong Chung Yin
Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115 (M.M.H., S.G.); and Division of General Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, NY (C.Y.K.).
Radiol Cardiothorac Imaging. 2021 Apr 15;3(2):e200523. doi: 10.1148/ryct.2021200523. eCollection 2021 Apr.
To evaluate nodule management guidelines in a simulated cohort of Lung Reporting and Data System (Lung-RADS) 4 nodules based on real-world data.
In this retrospective study, 100 000 patients were simulated from 151 patients with Lung-RADS 4 nodules (from January 2010 to August 2018). Each patient in the simulation was managed with each algorithm, and health outcomes were accumulated based on interventions and delays to cancer diagnosis. If the algorithm missed a cancer, it was diagnosed at the next annual screening round, although it would grow in the interim. Patient age-specific or cancer-specific mortality was assigned depending on whether the nodule was malignant, and quality-adjusted life years (QALYs) were calculated. Costs of interventions and cancer treatment were accumulated. One-way sensitivity analyses were performed.
The most effective algorithm was the British Thoracic Society (BTS; 10.041 QALYs), followed by the American College of Chest Physicians (10.035 QALYs) and Lung-RADS (10.021 QALYs). Only the BTS and Lung-RADS were on the efficient frontier, with an incremental cost-effectiveness ratio (ICER) of $52 634 (95% CI: $45 122, $60 619). Under nearly all sensitivity analyses, the only algorithms on the efficient frontier were BTS and Lung-RADS. The ICERs for BTS versus Lung-RADS were under $100 000 for all scenarios except an increased life expectancy in patients without cancer, in which case the ICER was $109 273.
The BTS algorithm and Lung-RADS were cost-effective for managing category 4 nodules, with BTS yielding greater QALYs.© RSNA, 2021See also the commentary by Elicker in this issue.
基于真实世界数据,评估在模拟的肺癌报告和数据系统(Lung-RADS)4类结节队列中的结节管理指南。
在这项回顾性研究中,从151例Lung-RADS 4类结节患者(2010年1月至2018年8月)中模拟出100000例患者。模拟队列中的每位患者均采用每种算法进行管理,并根据干预措施和癌症诊断延迟情况累积健康结局。如果算法漏诊了癌症,将在下一年度筛查时被诊断出来,尽管在此期间癌症会继续发展。根据结节是否为恶性分配患者的年龄特异性或癌症特异性死亡率,并计算质量调整生命年(QALY)。累积干预措施和癌症治疗的费用。进行单向敏感性分析。
最有效的算法是英国胸科学会(BTS;10.041 QALY)算法,其次是美国胸科医师学会(10.035 QALY)算法和Lung-RADS(10.021 QALY)算法。只有BTS算法和Lung-RADS算法处于有效前沿,增量成本效益比(ICER)为52634美元(95% CI:45122美元,60619美元)。在几乎所有敏感性分析中,处于有效前沿的唯一算法是BTS算法和Lung-RADS算法。除了无癌症患者预期寿命增加的情况(此时ICER为109273美元)外,在所有情况下,BTS算法与Lung-RADS算法的ICER均低于100000美元。
BTS算法和Lung-RADS算法在管理4类结节方面具有成本效益,BTS算法产生的QALY更高。© RSNA,2021另见本期Elicker的评论。