Cost Effectiveness Analysis of Lung Cancer Screening

描述（由申请人提供）：螺旋CT筛查检查可检测到常规胸片上看不到的无症状早期肺癌。这些发现正在推动CT肺癌筛查的直接面向消费者的营销，目标是能够支付自付费用的个人，希望显着降低他们死于肺癌的风险。用CT进行肺癌筛查并未显示出降低肺癌死亡率，但已显示出产生不必要的、危及生命的活检，以及由保险公司支付的大量下游医疗保健费用。即使没有CT筛查有效性的证据，政策制定者也在质疑其潜在的成本效益。我们提出了一个评估CT肺癌筛查的潜在成本效益的框架，该框架将具有更新的灵活性，以更好地了解技术和临床实践模式的变化。 我们建议的核心是一种新的肺癌自然史模型，该模型将用于估计由于肺癌筛查而导致的阶段转移和死亡率降低。我们的自然史模型将描述肺癌的生长速度和疾病进展到更晚期阶段的倾向，作为原发肿瘤大小的函数。它将被嵌入到一个更大的蒙特-卡罗模拟模型的美国人口进行肺癌筛查。蒙特-卡罗模型将模拟在其他筛查方案下的健康和经济结果，预测美国每年的肺癌发病率和死亡率趋势、5年生存率统计数据，并量化筛查在节省生命年数、资源利用和医疗保健成本方面的影响。将使用增量成本-效果分析，根据目标人群风险、开始和停止筛查的年龄以及筛查间隔确定主要筛查策略。

DESCRIPTION (provided by applicant): Helical CT screening examinations are detecting asymptomatic, early-stage lung cancer not seen on conventional chest radiographs. These findings are fueling direct-to-consumer marketing of CT lung cancer screening targeted to individuals who are able to pay out-of-pocket costs for the hope of significantly dropping their risk of death from lung cancer. Lung cancer screening with CT has not been shown to reduce lung cancer mortality, but has been shown to generate unnecessary, life-threatening biopsies, and large downstream health care costs that are paid out by insurers. Even without evidence of the effectiveness of CT screening, policy makers are questioning its potential cost-effectiveness. We propose a framework for evaluating the potential cost-effectiveness of CT lung cancer screening that will have the flexibility to be updated with an improved understanding of the technology and changes in clinical practice patterns. At the core of our proposal is a novel model of the natural history of lung cancer that will be used to estimate the stage-shift and the mortality reduction due to lung cancer screening. Our natural history model will describe the growth rate of lung cancer and the propensity of the disease to progress to more advanced stages as a function of the primary tumor size. It will be embedded into a larger Monte-Carlo simulation model of the US population undergoing lung cancer screening. The Monte-Carlo model will simulate health and economic outcomes under alternative screening scenarios and predict annual US lung cancer incidence and mortality trends, 5-year survival statistics, as well as quantify the impact of screening in terms life years saved, resource utilization and health care costs. An incremental cost-effectiveness analysis will be used to identify dominant screening strategies in terms of target population risk, ages to start and stop screening, and screening interval.