Applying causal inference methods to improve estimation of the real-world benefits and harms of lung cancer screening

应用因果推理方法来改进对肺癌筛查的现实益处和危害的估计

• 批准号: 10737187
• 负责人: Louise Henderson
• 金额: $ 34.86万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10737187
• 关键词: Address; Adherence; Affect; Behavioral; Behavioral Risk Factor Surveillance System; Breast Cancer Detection; Characteristics; Clinical Trials; Communication; Data; Data Set; Data Sources; Decision Aid; Decision Making; Development; Diagnostic Procedure; Early Diagnosis; Effectiveness; Eligibility Determination; Equilibrium; Female; General Population; Individual; Intervention; Left; Lung; Malignant Neoplasms; Malignant neoplasm of lung; Medicare claim; Methodology; Methods; National Cancer Institute; National Health Interview Survey; North Carolina; Observational Study; Outcome; Outcome Assessment; Patients; Pattern; Policy Maker; Population; Population Characteristics; Procedures; Provider; Randomized; Randomized, Controlled Trials; Recommendation; Registries; Research; Research Personnel; Risk Factors; Sampling; Screening for cancer; Selection Bias; Selection for Treatments; Smoking; Subgroup; Surveys; Time; United States Preventative Services Task Force; Update; Work; cancer therapy; clinical practice; colon cancer screening; cost; design; evidence base; follow-up; human old age (65+); improved; intervention effect; low dose computed tomography; lung cancer screening; mortality; novel; practice setting; randomized trial; routine screening; screening; screening guidelines; screening program; shared decision making; tool; trial enrollment; uptake

ABSTRACT Randomized controlled trials have demonstrated that low-dose computed tomography can substantially reduce lung cancer mortality, albeit at the cost of relatively high rates of false positives and complications from downstream procedures. However, systematic differences between trial and general populations eligible for lung cancer screening raise concerns about the relevance of trial findings for guiding the development and dissemination of lung cancer screening programs in clinical practice. Despite clear recommendations from the United States Preventative Services Task Force, lung cancer screening uptake and adherence remain low. Several studies have documented dramatic and selective attrition across the screening continuum – where about 10-20% of eligible individuals undergo lung cancer screening and of those, only about 40-60% are up-to- date with their annual screening at 15 months. When the benefits and harms of an intervention vary across subgroups and there is selective attrition, the balance of population-level benefits and harms is expected to change. As such, there is an urgent need to better characterize the effectiveness of lung cancer screening with low-dose computed tomography when applied to individuals outside of clinical trial settings. The primary objective of this proposal is to generate real-world evidence of the benefits and harms of lung cancer screening with low-dose computed tomography that explicitly considers the characteristics of populations at each step of the screening continuum, from the screening-eligible, to the screened, to the adherent. To address this objective, we will use cutting-edge causal inference methods, including trial transport and target trial emulation using real-world data, which can avoid the potential for time-related biases. To carry-out our proposed analyses, we will draw upon individual-level data from the randomized National Lung Screening Trial, as well as four real-world datasets including the National Health and Interview Survey, the Behavioral Risk Factors Surveillance Survey (Lung Cancer Screening Module), a 20% nationwide sample of Medicare claims, and the North Carolina Lung Screening Registry. Findings from this study will generate information about the effectiveness of lung cancer screening in real-world settings that can be used by patients, providers, and policymakers. This work will enhance the evidence base used by policymakers to update screening recommendations and refine decision aids to support communication with patients about screening net- benefits during shared decision-making. Ultimately, this work will support efforts to improve the delivery of lung cancer screening at the population level.

抽象的 随机对照试验表明，低剂量计算机断层扫描可以大大减少 肺癌死亡率，尽管以相对较高的假阳性率和并发症为代价 下游程序。但是，试验和一般人群之间的系统差异有资格 肺癌筛查引起了对试验结果与指导开发的相关性的担忧 在临床实践中传播肺癌筛查计划。尽管有明确的建议 美国预防服务工作队，肺癌筛查摄取和依从性仍然很低。 几项研究记录了整个筛选连续性的戏剧性和选择性属性 - 约有10-20％的合格个体接受肺癌筛查，其中只有大约40-60％是最新的 与15个月的年度筛查约会。当干预措施的益处和危害各不相同时 亚组和有选择性的属性，人口水平的福利和危害的平衡将有望 改变。因此，迫切需要更好地表征肺癌筛查的有效性 低剂量计算机断层扫描将应用于临床试验环境之外的个体。主要 该建议的目的是生成现实世界中的证据证明肺癌筛查的益处和危害 使用低剂量计算的层析成像，明确考虑了每个步骤的人群的特征 从符合筛选资格到筛选到粘合剂的筛选连续体。解决这个问题 目的，我们将使用尖端的因果推理方法，包括试验运输和目标试验仿真 使用现实世界中的数据，可以避免与时间相关的偏差的潜力。提出我们的建议 分析，我们还将借鉴随机国家肺筛查试验中的个人级别数据 作为四个现实世界中的数据集，包括国家健康和面试调查，行为风险因素 监视调查（肺癌筛查模块），20％的全国医疗保险索赔样本和 北卡罗来纳州肺部筛查注册中心。这项研究的发现将生成有关 肺癌筛查在现实环境中可以使用的有效性 决策者。这项工作将增强决策者用于更新筛查的证据基础 建议和完善决策辅助工具，以支持与患者筛查网络的沟通 - 共同决策期间的好处。最终，这项工作将支持改善肺部输送的努力 在人群水平上进行癌症筛查。